Exploring structure and function of sensory cortex with 7T MRI.

PubMed

Schluppeck, Denis; Sanchez-Panchuelo, Rosa-Maria; Francis, Susan T

2018-01-01

In this paper, we present an overview of 7T magnetic resonance imaging (MRI) studies of the detailed function and anatomy of sensory areas of the human brain. We discuss the motivation for the studies, with particular emphasis on increasing the spatial resolution of functional MRI (fMRI) using reduced field-of-view (FOV) data acquisitions. MRI at ultra-high-field (UHF) - defined here as 7T and above - has several advantages over lower field strengths. The intrinsic signal-to-noise ratio (SNR) of images is higher at UHF, and coupled with the increased blood-oxygen-level-dependent (BOLD) signal change, this results in increased BOLD contrast-to-noise ratio (CNR), which can be exploited to improve spatial resolution or detect weaker signals. Additionally, the BOLD signal from the intra-vascular (IV) compartment is relatively diminished compared to lower field strengths. Together, these properties make 7T functional MRI an attractive proposition for high spatial specificity measures. But with the advantages come some challenges. For example, increased vulnerability to susceptibility-induced geometric distortions and signal loss in EPI acquisitions tend to be much larger. Some of these technical issues can be addressed with currently available tools and will be discussed. We highlight the key methodological considerations for high resolution functional and structural imaging at 7 T. We then present recent data using the high spatial resolution available at UHF in studies of the visual and somatosensory cortex to highlight promising developments in this area. Copyright © 2017 Elsevier Inc. All rights reserved.

Hemispheric asymmetries in dorsal language pathway white-matter tracts: A magnetic resonance imaging tractography and functional magnetic resonance imaging study.

PubMed

Silva, Guilherme; Citterio, Alberto

2017-10-01

Introduction Previous studies have shown that the arcuate fasciculus has a leftward asymmetry in right-handers that could be correlated with the language lateralisation defined by functional magnetic resonance imaging. Nonetheless, information about the asymmetry of the other fibres that constitute the dorsal language pathway is scarce. Objectives This study investigated the asymmetry of the white-matter tracts involved in the dorsal language pathway through the diffusion tensor imaging (DTI) technique, in relation to language hemispheric dominance determined by task-dependent functional magnetic resonance imaging (fMRI). Methods We selected 11 patients (10 right-handed) who had been studied with task-dependent fMRI for language areas and DTI and who had no language impairment or structural abnormalities that could compromise magnetic resonance tractography of the fibres involved in the dorsal language pathway. Laterality indices (LI) for fMRI and for the volumes of each tract were calculated. Results In fMRI, all the right-handers had left hemispheric lateralisation, and the ambidextrous subject presented right hemispheric dominance. The arcuate fasciculus LI was strongly correlated with fMRI LI ( r = 0.739, p = 0.009), presenting the same lateralisation of fMRI in seven subjects (including the right hemispheric dominant). It was not asymmetric in three cases and had opposite lateralisation in one case. The other tracts presented predominance for rightward lateralisation, especially superior longitudinal fasciculus (SLF) II/III (nine subjects), but their LI did not correlate (directly or inversely) with fMRI LI. Conclusion The fibres that constitute the dorsal language pathway have an asymmetric distribution in the cerebral hemispheres. Only the asymmetry of the arcuate fasciculus is correlated with fMRI language lateralisation.

On the feasibility of concurrent human TMS-EEG-fMRI measurements

PubMed Central

Reithler, Joel; Schuhmann, Teresa; de Graaf, Tom; Uludağ, Kâmil; Goebel, Rainer; Sack, Alexander T.

2013-01-01

Simultaneously combining the complementary assets of EEG, functional MRI (fMRI), and transcranial magnetic stimulation (TMS) within one experimental session provides synergetic results, offering insights into brain function that go beyond the scope of each method when used in isolation. The steady increase of concurrent EEG-fMRI, TMS-EEG, and TMS-fMRI studies further underlines the added value of such multimodal imaging approaches. Whereas concurrent EEG-fMRI enables monitoring of brain-wide network dynamics with high temporal and spatial resolution, the combination with TMS provides insights in causal interactions within these networks. Thus the simultaneous use of all three methods would allow studying fast, spatially accurate, and distributed causal interactions in the perturbed system and its functional relevance for intact behavior. Concurrent EEG-fMRI, TMS-EEG, and TMS-fMRI experiments are already technically challenging, and the three-way combination of TMS-EEG-fMRI might yield additional difficulties in terms of hardware strain or signal quality. The present study explored the feasibility of concurrent TMS-EEG-fMRI studies by performing safety and quality assurance tests based on phantom and human data combining existing commercially available hardware. Results revealed that combined TMS-EEG-fMRI measurements were technically feasible, safe in terms of induced temperature changes, allowed functional MRI acquisition with comparable image quality as during concurrent EEG-fMRI or TMS-fMRI, and provided artifact-free EEG before and from 300 ms after TMS pulse application. Based on these empirical findings, we discuss the conceptual benefits of this novel complementary approach to investigate the working human brain and list a number of precautions and caveats to be heeded when setting up such multimodal imaging facilities with current hardware. PMID:23221407

Sporadic Inclusion Body Myositis: MRI Findings and Correlation With Clinical and Functional Parameters.

PubMed

Guimaraes, Julio Brandao; Zanoteli, Edmar; Link, Thomas M; de Camargo, Leonardo V; Facchetti, Luca; Nardo, Lorenzo; Fernandes, Artur da Rocha Correa

2017-12-01

The purpose of this prospective study is to assess MRI findings in patients with sporadic inclusion body myositis (IBM) and correlate them with clinical and functional parameters. This study included 12 patients with biopsy-proven sporadic IBM. All patients underwent MRI of the bilateral upper and lower extremities. The images were scored for muscle atrophy, fatty infiltration, and edema pattern. Clinical data included onset and duration of disease. Muscle strength was measured using the Medical Research Council (MRC) scale, and functional status was assessed using the Modified Rankin Scale. Correlation between MRI and different clinical and functional parameters was calculated using the Spearman rank test and Pearson correlation. All patients showed MRI abnormalities, which were more severe within the lower limbs and the distal segments. The most prevalent MRI finding was fat infiltration. There was a statistically significant correlation between disease duration and number of muscles infiltrated by fat (r = 0.65; p = 0.04). The number of muscles with fat infiltration correlated with the sum of the scores of MRC (r = -0.60; p = 0.04) and with the Modified Rankin Scale (r = 0.48; p = 0.03). Our findings suggest that most patients with biopsy-proven sporadic IBM present with a typical pattern of muscle involvement at MRI, more extensively in the lower extremities. Moreover, MRI findings strongly correlated with clinical and functional parameters, because both the extent and severity of muscle involvement assessed by MRI and clinical and functional parameters are associated with the early onset of the disease and its duration.

A new vibrator to stimulate muscle proprioceptors in fMRI.

PubMed

Montant, Marie; Romaiguère, Patricia; Roll, Jean-Pierre

2009-03-01

Studying cognitive brain functions by functional magnetic resonance imaging (fMRI) requires appropriate stimulation devices that do not interfere with the magnetic fields. Since the emergence of fMRI in the 90s, a number of stimulation devices have been developed for the visual and auditory modalities. Only few devices, however, have been developed for the somesthesic modality. Here, we present a vibration device for studying somesthesia that is compatible with high magnetic field environments and that can be used in fMRI machines. This device consists of a poly vinyl chloride (PVC) vibrator containing a wind turbine and of a pneumatic apparatus that controls 1-6 vibrators simultaneously. Just like classical electromagnetic vibrators, our device stimulates muscle mechanoreceptors (muscle spindles) and generates reliable illusions of movement. We provide the fMRI compatibility data (phantom test), the calibration curve (vibration frequency as a function of air flow), as well as the results of a kinesthetic test (perceived speed of the illusory movement as a function of vibration frequency). This device was used successfully in several brain imaging studies using both fMRI and magnetoencephalography.

Optimized Design and Analysis of Sparse-Sampling fMRI Experiments

PubMed Central

Perrachione, Tyler K.; Ghosh, Satrajit S.

2013-01-01

Sparse-sampling is an important methodological advance in functional magnetic resonance imaging (fMRI), in which silent delays are introduced between MR volume acquisitions, allowing for the presentation of auditory stimuli without contamination by acoustic scanner noise and for overt vocal responses without motion-induced artifacts in the functional time series. As such, the sparse-sampling technique has become a mainstay of principled fMRI research into the cognitive and systems neuroscience of speech, language, hearing, and music. Despite being in use for over a decade, there has been little systematic investigation of the acquisition parameters, experimental design considerations, and statistical analysis approaches that bear on the results and interpretation of sparse-sampling fMRI experiments. In this report, we examined how design and analysis choices related to the duration of repetition time (TR) delay (an acquisition parameter), stimulation rate (an experimental design parameter), and model basis function (an analysis parameter) act independently and interactively to affect the neural activation profiles observed in fMRI. First, we conducted a series of computational simulations to explore the parameter space of sparse design and analysis with respect to these variables; second, we validated the results of these simulations in a series of sparse-sampling fMRI experiments. Overall, these experiments suggest the employment of three methodological approaches that can, in many situations, substantially improve the detection of neurophysiological response in sparse fMRI: (1) Sparse analyses should utilize a physiologically informed model that incorporates hemodynamic response convolution to reduce model error. (2) The design of sparse fMRI experiments should maintain a high rate of stimulus presentation to maximize effect size. (3) TR delays of short to intermediate length can be used between acquisitions of sparse-sampled functional image volumes to increase the number of samples and improve statistical power. PMID:23616742

Functional magnetic resonance imaging in clinical practice: State of the art and science.

PubMed

Barras, Christen D; Asadi, Hamed; Baldeweg, Torsten; Mancini, Laura; Yousry, Tarek A; Bisdas, Sotirios

2016-11-01

Functional magnetic resonance imaging (fMRI) has become a mainstream neuroimaging modality in the assessment of patients being evaluated for brain tumour and epilepsy surgeries. Thus, it is important for doctors in primary care settings to be well acquainted with the present and potential future applications, as well as limitations, of this modality. The objective of this article is to introduce the theoretical principles and state-of-the-art clinical applications of fMRI in brain tumour and epilepsy surgery, with a focus on the implications for clinical primary care. fMRI enables non-invasive functional mapping of specific cortical tasks (eg motor, language, memory-based, visual), revealing information about functional localisation, anatomical variation in cortical function, and disease effects and adaptations, including the fascinating phenomenon of brain plasticity. fMRI is currently ordered by specialist neurologists and neurosurgeons for the purposes of pre-surgical assessment, and within the context of an experienced multidisciplinary team to prepare, conduct and interpret the scan. With an increasing number of patients undergoing fMRI, general practitioners can expect questions about the current and emerging role of fMRI in clinical care from these patients and their families.

Haptic fMRI: Reliability and performance of electromagnetic haptic interfaces for motion and force neuroimaging experiments.

PubMed

Menon, Samir; Zhu, Jack; Goyal, Deeksha; Khatib, Oussama

2017-07-01

Haptic interfaces compatible with functional magnetic resonance imaging (Haptic fMRI) promise to enable rich motor neuroscience experiments that study how humans perform complex manipulation tasks. Here, we present a large-scale study (176 scans runs, 33 scan sessions) that characterizes the reliability and performance of one such electromagnetically actuated device, Haptic fMRI Interface 3 (HFI-3). We outline engineering advances that ensured HFI-3 did not interfere with fMRI measurements. Observed fMRI temporal noise levels with HFI-3 operating were at the fMRI baseline (0.8% noise to signal). We also present results from HFI-3 experiments demonstrating that high resolution fMRI can be used to study spatio-temporal patterns of fMRI blood oxygenation dependent (BOLD) activation. These experiments include motor planning, goal-directed reaching, and visually-guided force control. Observed fMRI responses are consistent with existing literature, which supports Haptic fMRI's effectiveness at studying the brain's motor regions.

Functional imaging of sleep vertex sharp transients.

PubMed

Stern, John M; Caporro, Matteo; Haneef, Zulfi; Yeh, Hsiang J; Buttinelli, Carla; Lenartowicz, Agatha; Mumford, Jeanette A; Parvizi, Josef; Poldrack, Russell A

2011-07-01

The vertex sharp transient (VST) is an electroencephalographic (EEG) discharge that is an early marker of non-REM sleep. It has been recognized since the beginning of sleep physiology research, but its source and function remain mostly unexplained. We investigated VST generation using functional MRI (fMRI). Simultaneous EEG and fMRI were recorded from seven individuals in drowsiness and light sleep. VST occurrences on EEG were modeled with fMRI using an impulse function convolved with a hemodynamic response function to identify cerebral regions correlating to the VSTs. A resulting statistical image was thresholded at Z>2.3. Two hundred VSTs were identified. Significantly increased signal was present bilaterally in medial central, lateral precentral, posterior superior temporal, and medial occipital cortex. No regions of decreased signal were present. The regions are consistent with electrophysiologic evidence from animal models and functional imaging of human sleep, but the results are specific to VSTs. The regions principally encompass the primary sensorimotor cortical regions for vision, hearing, and touch. The results depict a network comprising the presumed VST generator and its associated regions. The associated regions functional similarity for primary sensation suggests a role for VSTs in sensory experience during sleep. Copyright © 2011 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Sodium MRI: Methods and applications

PubMed Central

Madelin, Guillaume; Lee, Jae-Seung; Regatte, Ravinder R.; Jerschow, Alexej

2014-01-01

Sodium NMR spectroscopy and MRI have become popular in recent years through the increased availability of high-field MRI scanners, advanced scanner hardware and improved methodology. Sodium MRI is being evaluated for stroke and tumor detection, for breast cancer studies, and for the assessment of osteoarthritis and muscle and kidney functions, to name just a few. In this article, we aim to present an up-to-date review of the theoretical background, the methodology, the challenges and limitations, and current and potential new applications of sodium MRI. PMID:24815363

Functional and structural abnormalities associated with empathy in patients with schizophrenia: An fMRI and VBM study

PubMed Central

Singh, Sadhana; Modi, Shilpi; Goyal, Satnam; Kaur, Prabhjot; Singh, Namita; Bhatia, Triptish; Deshpande, Smita N; Khushu, Subash

2016-01-01

Empathy deficit is a core feature of schizophrenia which may lead to social dysfunction. The present study was carried out to investigate functional and structural abnormalities associated with empathy in patients with schizophrenia using functional magnetic resonance imaging (fMRI) and voxel-based morphometry (VBM). A sample of 14 schizophrenia patients and 14 healthy control subjects matched for age, sex and education were examined with structural high-resolution T1-weighted MRI; fMRI images were obtained during empathy task in the same session. The analysis was carried out using SPM8 software. On behavioural assessment, schizophrenic patients (83.00±29.04) showed less scores for sadness compared to healthy controls (128.70±22.26) (p<0.001). fMRI results also showed reduced clusters of activation in the bilateral fusiform gyrus, left lingual gyrus, left middle and inferior occipital gyrus in schizophrenic subjects as compared to controls during empathy task. In the same brain areas, VBM results also showed reduced grey and white matter volumes. The present study provides an evidence for an association between structural alterations and disturbed functional brain activation during empathy task in persons affected with schizophrenia. These findings suggest a biological basis for social cognition deficits in schizophrenics. PMID:25963262

Functional and structural abnormalities associated with empathy in patients with schizophrenia: An fMRI and VBM study.

PubMed

Singh, Sadhana; Modi, Shilpi; Goyal, Satnam; Kaur, Prabhjot; Singh, Namita; Bhatia, Triptish; Deshpande, Smita N; Khushu, Subash

2015-06-01

Empathy deficit is a core feature of schizophrenia which may lead to social dysfunction. The present study was carried out to investigate functional and structural abnormalities associated with empathy in patients with schizophrenia using functional magnetic resonance imaging (fMRI) and voxel-based morphometry (VBM). A sample of 14 schizophrenia patients and 14 healthy control subjects matched for age, sex and education were examined with structural highresolution T1-weighted MRI; fMRI images were obtained during empathy task in the same session. The analysis was carried out using SPM8 software. On behavioural assessment, schizophrenic patients (83.00+-29.04) showed less scores for sadness compared to healthy controls (128.70+-22.26) (p less than 0.001). fMRI results also showed reduced clusters of activation in the bilateral fusiform gyrus, left lingual gyrus, left middle and inferior occipital gyrus in schizophrenic subjects as compared to controls during empathy task. In the same brain areas, VBM results also showed reduced grey and white matter volumes. The present study provides an evidence for an association between structural alterations and disturbed functional brain activation during empathy task in persons affected with schizophrenia. These findings suggest a biological basis for social cognition deficits in schizophrenics.

Connectivity changes after laser ablation: Resting-state fMRI.

PubMed

Boerwinkle, Varina L; Vedantam, Aditya; Lam, Sandi; Wilfong, Angus A; Curry, Daniel J

2018-05-01

Resting-state functional magnetic resonance imaging (rsfMRI) is emerging as a useful tool in the multimodal assessment of patients with epilepsy. In pediatric patients who cannot perform task-based fMRI, rsfMRI may present an adjunct and alternative. Although changes in brain activation during task-based fMRI have been described after surgery for epilepsy, there is limited data on the role of postoperative rsfMRI. In this short review, we discuss the role of postoperative rsfMRI after laser ablation of seizure foci. By establishing standardized anesthesia protocols and imaging parameters, we have been able to perform serial rsfMRI at postoperative follow-up. The development of in-house software that can merge rsfMRI images to surgical navigation systems has allowed us to enhance the clinical applications of this technique. Resting-state fMRI after laser ablation has the potential to identify changes in connectivity, localize new seizure foci, and guide antiepileptic therapy. In our experience, rsfMRI complements conventional MR imaging and task-based fMRI for the evaluation of patients with seizure recurrence after laser ablation, and represents a potential noninvasive biomarker for functional connectivity. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

MRI-based morphometric characterizations of sexual dimorphism of the cerebrum of ferrets (Mustela putorius).

PubMed

Sawada, Kazuhiko; Horiuchi-Hirose, Miwa; Saito, Shigeyoshi; Aoki, Ichio

2013-12-01

The present study aimed to characterize cerebral morphology in young adult ferrets and its sexual dimorphism using high-field MRI and MRI-based morphometry. Ex vivo short TR/TE (typical T1-weighted parameter setting for conventional MRI) and T2W (long TR/TE) MRI with high spatial resolution at 7-tesla could visualize major subcortical and archicortical structures, i.e., the caudate nucleus, lentiform nucleus, amygdala and hippocampus. In particular, laminar organization of the olfactory bulb was identifiable by short TR/TE-MRI. The primary and secondary sulci observable in the adult ferret were distinguishable on either short TR/TE- or T2W-MRI, and the cortical surface morphology was reproduced well by 3D-rendered images obtained by short TR/TE-MRI. The cerebrum had a significantly lower volume in females than in males, which was attributed to region-specific volume reduction in the cerebral cortex and subcortical white matter in females. A sexual difference was also detected, manifested by an overall reduction in normalized signal ratios of short TR/TE-MRI in all cerebral structures examined in females than in males. On the other hand, an alternating array of higher and lower short TR/TE-MRI intensity transverse zones throughout the cortex, which was reminiscent of the functional cortical areas, was revealed by maximum intensity projection (MIP) in 3D. The normalized signal ratio of short TR/TE-MRI, but not T2W-MRI in the cortex, was negatively correlated with the density of myelin-basic protein immunoreactive fibers (males, r=-0.440; females, r=-0.481). The present results suggest that sexual differences in the adult ferret cerebrum are characterized by reduced volumes of the cerebral cortex and subcortical white matter in females, and by overall reductions in physiochemical characteristics, as obtained by short TR/TE-MRI, in females. It should be noted that short TR/TE-MRI-based MIP delineated functional cortical areas related to myeloarchitecture in 3D. Such an approach makes possible conventional investigation of the functional organization of the cerebral cortex and its abnormalities using high-field MRI. Copyright © 2013 Elsevier Inc. All rights reserved.

Functional Imaging of the Lungs with Gas Agents

PubMed Central

Kruger, Stanley J.; Nagle, Scott K.; Couch, Marcus J.; Ohno, Yoshiharu; Albert, Mitchell; Fain, Sean B.

2015-01-01

This review focuses on the state-of-the-art of the three major classes of gas contrast agents used in magnetic resonance imaging (MRI) – hyperpolarized (HP) gas, molecular oxygen, and fluorinated gas – and their application to clinical pulmonary research. During the past several years there has been accelerated development of pulmonary MRI. This has been driven in part by concerns regarding ionizing radiation using multi-detector computed tomography (CT). However, MRI also offers capabilities for fast multi-spectral and functional imaging using gas agents that are not technically feasible with CT. Recent improvements in gradient performance and radial acquisition methods using ultra-short echo time (UTE) have contributed to advances in these functional pulmonary MRI techniques. Relative strengths and weaknesses of the main functional imaging methods and gas agents are compared and applications to measures of ventilation, diffusion, and gas exchange are presented. Functional lung MRI methods using these gas agents are improving our understanding of a wide range of chronic lung diseases, including chronic obstructive pulmonary disease (COPD), asthma, and cystic fibrosis (CF) in both adults and children. PMID:26218920

Network analysis of EEG related functional MRI changes due to medication withdrawal in focal epilepsy

PubMed Central

Hermans, Kees; Ossenblok, Pauly; van Houdt, Petra; Geerts, Liesbeth; Verdaasdonk, Rudolf; Boon, Paul; Colon, Albert; de Munck, Jan C.

2015-01-01

Anti-epileptic drugs (AEDs) have a global effect on the neurophysiology of the brain which is most likely reflected in functional brain activity recorded with EEG and fMRI. These effects may cause substantial inter-subject variability in studies where EEG correlated functional MRI (EEG–fMRI) is used to determine the epileptogenic zone in patients who are candidate for epilepsy surgery. In the present study the effects on resting state fMRI are quantified in conditions with AED administration and after withdrawal of AEDs. EEG–fMRI data were obtained from 10 patients in the condition that the patient was on the steady-state maintenance doses of AEDs as prescribed (condition A) and after withdrawal of AEDs (condition B), at the end of a clinically standard pre-surgical long term video-EEG monitoring session. Resting state networks (RSN) were extracted from fMRI. The epileptic component (ICE) was identified by selecting the RSN component with the largest overlap with the EEG–fMRI correlation pattern. Changes in RSN functional connectivity between conditions A and B were quantified. EEG–fMRI correlation analysis was successful in 30% and 100% of the cases in conditions A and B, respectively. Spatial patterns of ICEs are comparable in conditions A and B, except for one patient for whom it was not possible to identify the ICE in condition A. However, the resting state functional connectivity is significantly increased in the condition after withdrawal of AEDs (condition B), which makes resting state fMRI potentially a new tool to study AED effects. The difference in sensitivity of EEG–fMRI in conditions A and B, which is not related to the number of epileptic EEG events occurring during scanning, could be related to the increased functional connectivity in condition B. PMID:26137444

Using fMRI to study reward processing in humans: past, present, and future

PubMed Central

Wang, Kainan S.; Smith, David V.

2016-01-01

Functional magnetic resonance imaging (fMRI) is a noninvasive tool used to probe cognitive and affective processes. Although fMRI provides indirect measures of neural activity, the advent of fMRI has allowed for 1) the corroboration of significant animal findings in the human brain, and 2) the expansion of models to include more common human attributes that inform behavior. In this review, we briefly consider the neural basis of the blood oxygenation level dependent signal to set up a discussion of how fMRI studies have applied it in examining cognitive models in humans and the promise of using fMRI to advance such models. Specifically, we illustrate the contribution that fMRI has made to the study of reward processing, focusing on the role of the striatum in encoding reward-related learning signals that drive anticipatory and consummatory behaviors. For instance, we discuss how fMRI can be used to link neural signals (e.g., striatal responses to rewards) to individual differences in behavior and traits. While this functional segregation approach has been constructive to our understanding of reward-related functions, many fMRI studies have also benefitted from a functional integration approach that takes into account how interconnected regions (e.g., corticostriatal circuits) contribute to reward processing. We contend that future work using fMRI will profit from using a multimodal approach, such as combining fMRI with noninvasive brain stimulation tools (e.g., transcranial electrical stimulation), that can identify causal mechanisms underlying reward processing. Consequently, advancements in implementing fMRI will promise new translational opportunities to inform our understanding of psychopathologies. PMID:26740530

Individual Brain Charting, a high-resolution fMRI dataset for cognitive mapping.

PubMed

Pinho, Ana Luísa; Amadon, Alexis; Ruest, Torsten; Fabre, Murielle; Dohmatob, Elvis; Denghien, Isabelle; Ginisty, Chantal; Becuwe-Desmidt, Séverine; Roger, Séverine; Laurier, Laurence; Joly-Testault, Véronique; Médiouni-Cloarec, Gaëlle; Doublé, Christine; Martins, Bernadette; Pinel, Philippe; Eger, Evelyn; Varoquaux, Gaël; Pallier, Christophe; Dehaene, Stanislas; Hertz-Pannier, Lucie; Thirion, Bertrand

2018-06-12

Functional Magnetic Resonance Imaging (fMRI) has furthered brain mapping on perceptual, motor, as well as higher-level cognitive functions. However, to date, no data collection has systematically addressed the functional mapping of cognitive mechanisms at a fine spatial scale. The Individual Brain Charting (IBC) project stands for a high-resolution multi-task fMRI dataset that intends to provide the objective basis toward a comprehensive functional atlas of the human brain. The data refer to a cohort of 12 participants performing many different tasks. The large amount of task-fMRI data on the same subjects yields a precise mapping of the underlying functions, free from both inter-subject and inter-site variability. The present article gives a detailed description of the first release of the IBC dataset. It comprises a dozen of tasks, addressing both low- and high- level cognitive functions. This openly available dataset is thus intended to become a reference for cognitive brain mapping.

Sparse representation of whole-brain fMRI signals for identification of functional networks.

PubMed

Lv, Jinglei; Jiang, Xi; Li, Xiang; Zhu, Dajiang; Chen, Hanbo; Zhang, Tuo; Zhang, Shu; Hu, Xintao; Han, Junwei; Huang, Heng; Zhang, Jing; Guo, Lei; Liu, Tianming

2015-02-01

There have been several recent studies that used sparse representation for fMRI signal analysis and activation detection based on the assumption that each voxel's fMRI signal is linearly composed of sparse components. Previous studies have employed sparse coding to model functional networks in various modalities and scales. These prior contributions inspired the exploration of whether/how sparse representation can be used to identify functional networks in a voxel-wise way and on the whole brain scale. This paper presents a novel, alternative methodology of identifying multiple functional networks via sparse representation of whole-brain task-based fMRI signals. Our basic idea is that all fMRI signals within the whole brain of one subject are aggregated into a big data matrix, which is then factorized into an over-complete dictionary basis matrix and a reference weight matrix via an effective online dictionary learning algorithm. Our extensive experimental results have shown that this novel methodology can uncover multiple functional networks that can be well characterized and interpreted in spatial, temporal and frequency domains based on current brain science knowledge. Importantly, these well-characterized functional network components are quite reproducible in different brains. In general, our methods offer a novel, effective and unified solution to multiple fMRI data analysis tasks including activation detection, de-activation detection, and functional network identification. Copyright © 2014 Elsevier B.V. All rights reserved.

[Functional magnetic resonance imaging. What are the benefits expected in hand surgery?].

PubMed

Moutet, F; Delon-Martin, C; Martin, O; Sirigu, A; Delaquaize, F; Benali, H; Masquelet, A-C

2013-06-01

Functional MRI (fMRI) allowed considerable advances upon understanding of cerebral functioning. Cortical plasticity, which allows the voluntary command of a restored function by a transferred muscle remains to be investigated in its intimacy. The authors present here the round table held at the 48th annual meeting of the French Society for Surgery of the Hand on December 22nd, 2012. It tries to review the analysis of the phenomenon observed during multiple tendinous transfers for restoration of proximal radial nerve palsy. Were successively approached: 1) Methods of acquisition and analysis of the signals (C. D-M.); 2) Movement reorganization (O.M.); 3) Motor plasticity after hand allograft (A. S.); 4) The potential interest of the fMRI in hand rehabilitation (F. D.); 5) The analysis of cerebral plasticity in general (H. B.). A rather philosophical conclusion opens other fields to f MRI (A.M.). Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Visual imagery and functional connectivity in blindness: a single-case study

PubMed Central

Boucard, Christine C.; Rauschecker, Josef P.; Neufang, Susanne; Berthele, Achim; Doll, Anselm; Manoliu, Andrej; Riedl, Valentin; Sorg, Christian; Wohlschläger, Afra; Mühlau, Mark

2016-01-01

We present a case report on visual brain plasticity after total blindness acquired in adulthood. SH lost her sight when she was 27. Despite having been totally blind for 43 years, she reported to strongly rely on her vivid visual imagery. Three-Tesla magnetic resonance imaging (MRI) of SH and age-matched controls was performed. The MRI sequence included anatomical MRI, resting-state functional MRI, and task-related functional MRI where SH was instructed to imagine colours, faces, and motion. Compared to controls, voxel-based analysis revealed white matter loss along SH's visual pathway as well as grey matter atrophy in the calcarine sulci. Yet we demonstrated activation in visual areas, including V1, using functional MRI. Of the four identified visual resting-state networks, none showed alterations in spatial extent; hence, SH's preserved visual imagery seems to be mediated by intrinsic brain networks of normal extent. Time courses of two of these networks showed increased correlation with that of the inferior posterior default mode network, which may reflect adaptive changes supporting SH's strong internal visual representations. Overall, our findings demonstrate that conscious visual experience is possible even after years of absence of extrinsic input. PMID:25690326

Visual imagery and functional connectivity in blindness: a single-case study.

PubMed

Boucard, Christine C; Rauschecker, Josef P; Neufang, Susanne; Berthele, Achim; Doll, Anselm; Manoliu, Andrej; Riedl, Valentin; Sorg, Christian; Wohlschläger, Afra; Mühlau, Mark

2016-05-01

We present a case report on visual brain plasticity after total blindness acquired in adulthood. SH lost her sight when she was 27. Despite having been totally blind for 43 years, she reported to strongly rely on her vivid visual imagery. Three-Tesla magnetic resonance imaging (MRI) of SH and age-matched controls was performed. The MRI sequence included anatomical MRI, resting-state functional MRI, and task-related functional MRI where SH was instructed to imagine colours, faces, and motion. Compared to controls, voxel-based analysis revealed white matter loss along SH's visual pathway as well as grey matter atrophy in the calcarine sulci. Yet we demonstrated activation in visual areas, including V1, using functional MRI. Of the four identified visual resting-state networks, none showed alterations in spatial extent; hence, SH's preserved visual imagery seems to be mediated by intrinsic brain networks of normal extent. Time courses of two of these networks showed increased correlation with that of the inferior posterior default mode network, which may reflect adaptive changes supporting SH's strong internal visual representations. Overall, our findings demonstrate that conscious visual experience is possible even after years of absence of extrinsic input.

Diffusion and perfusion weighted magnetic resonance imaging for tumor volume definition in radiotherapy of brain tumors.

PubMed

Guo, Lu; Wang, Gang; Feng, Yuanming; Yu, Tonggang; Guo, Yu; Bai, Xu; Ye, Zhaoxiang

2016-09-21

Accurate target volume delineation is crucial for the radiotherapy of tumors. Diffusion and perfusion magnetic resonance imaging (MRI) can provide functional information about brain tumors, and they are able to detect tumor volume and physiological changes beyond the lesions shown on conventional MRI. This review examines recent studies that utilized diffusion and perfusion MRI for tumor volume definition in radiotherapy of brain tumors, and it presents the opportunities and challenges in the integration of multimodal functional MRI into clinical practice. The results indicate that specialized and robust post-processing algorithms and tools are needed for the precise alignment of targets on the images, and comprehensive validations with more clinical data are important for the improvement of the correlation between histopathologic results and MRI parameter images.

Detection of early subclinical lung disease in children with cystic fibrosis by lung ventilation imaging with hyperpolarised gas MRI.

PubMed

Marshall, Helen; Horsley, Alex; Taylor, Chris J; Smith, Laurie; Hughes, David; Horn, Felix C; Swift, Andrew J; Parra-Robles, Juan; Hughes, Paul J; Norquay, Graham; Stewart, Neil J; Collier, Guilhem J; Teare, Dawn; Cunningham, Steve; Aldag, Ina; Wild, Jim M

2017-08-01

Hyperpolarised 3 He ventilation-MRI, anatomical lung MRI, lung clearance index (LCI), low-dose CT and spirometry were performed on 19 children (6-16 years) with clinically stable mild cystic fibrosis (CF) (FEV 1 >-1.96), and 10 controls. All controls had normal spirometry, MRI and LCI. Ventilation-MRI was the most sensitive method of detecting abnormalities, present in 89% of patients with CF, compared with CT abnormalities in 68%, LCI 47% and conventional MRI 22%. Ventilation defects were present in the absence of CT abnormalities and in patients with normal physiology, including LCI. Ventilation-MRI is thus feasible in young children, highly sensitive and provides additional information about lung structure-function relationships. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Morphological and functional evaluation of chronic pancreatitis with magnetic resonance imaging

PubMed Central

Hansen, Tine Maria; Nilsson, Matias; Gram, Mikkel; Frøkjær, Jens Brøndum

2013-01-01

Magnetic resonance imaging (MRI) techniques for assessment of morphology and function of the pancreas have been improved dramatically the recent years and MRI is very often used in diagnosing and follow-up of chronic pancreatitis (CP) patients. Standard MRI including fat-suppressed T1-weighted and T2-weighted imaging techniques reveal decreased signal and glandular atrophy of the pancreas in CP. In contrast-enhanced MRI of the pancreas in CP the pancreatic signal is usually reduced and delayed due to decreased perfusion as a result of chronic inflammation and fibrosis. Thus, morphological changes of the ductal system can be assessed by magnetic resonance cholangiopancreatography (MRCP). Furthermore, secretin-stimulated MRCP is a valuable technique to evaluate side branch pathology and the exocrine function of the pancreas and diffusion weighted imaging can be used to quantify both parenchymal fibrotic changes and the exocrine function of the pancreas. These standard and advanced MRI techniques are supplementary techniques to reveal morphological and functional changes of the pancreas in CP. Recently, spectroscopy has been used for assessment of metabolite concentrations in-vivo in different tissues and may have the potential to offer better tissue characterization of the pancreas. Hence, the purpose of the present review is to provide an update on standard and advanced MRI techniques of the pancreas in CP. PMID:24259954

Functional Connectivity Mapping in the Animal Model: Principles and Applications of Resting-State fMRI

PubMed Central

Gorges, Martin; Roselli, Francesco; Müller, Hans-Peter; Ludolph, Albert C.; Rasche, Volker; Kassubek, Jan

2017-01-01

“Resting-state” fMRI has substantially contributed to the understanding of human and non-human functional brain organization by the analysis of correlated patterns in spontaneous activity within dedicated brain systems. Spontaneous neural activity is indirectly measured from the blood oxygenation level-dependent signal as acquired by echo planar imaging, when subjects quietly “resting” in the scanner. Animal models including disease or knockout models allow a broad spectrum of experimental manipulations not applicable in humans. The non-invasive fMRI approach provides a promising tool for cross-species comparative investigations. This review focuses on the principles of “resting-state” functional connectivity analysis and its applications to living animals. The translational aspect from in vivo animal models toward clinical applications in humans is emphasized. We introduce the fMRI-based investigation of the non-human brain’s hemodynamics, the methodological issues in the data postprocessing, and the functional data interpretation from different abstraction levels. The longer term goal of integrating fMRI connectivity data with structural connectomes obtained with tracing and optical imaging approaches is presented and will allow the interrogation of fMRI data in terms of directional flow of information and may identify the structural underpinnings of observed functional connectivity patterns. PMID:28539914

Resting-State Seed-Based Analysis: An Alternative to Task-Based Language fMRI and Its Laterality Index.

PubMed

Smitha, K A; Arun, K M; Rajesh, P G; Thomas, B; Kesavadas, C

2017-06-01

Language is a cardinal function that makes human unique. Preservation of language function poses a great challenge for surgeons during resection. The aim of the study was to assess the efficacy of resting-state fMRI in the lateralization of language function in healthy subjects to permit its further testing in patients who are unable to perform task-based fMRI. Eighteen healthy right-handed volunteers were prospectively evaluated with resting-state fMRI and task-based fMRI to assess language networks. The laterality indices of Broca and Wernicke areas were calculated by using task-based fMRI via a voxel-value approach. We adopted seed-based resting-state fMRI connectivity analysis together with parameters such as amplitude of low-frequency fluctuation and fractional amplitude of low-frequency fluctuation (fALFF). Resting-state fMRI connectivity maps for language networks were obtained from Broca and Wernicke areas in both hemispheres. We performed correlation analysis between the laterality index and the z scores of functional connectivity, amplitude of low-frequency fluctuation, and fALFF. Pearson correlation analysis between signals obtained from the z score of fALFF and the laterality index yielded a correlation coefficient of 0.849 ( P < .05). Regression analysis of the fALFF with the laterality index yielded an R 2 value of 0.721, indicating that 72.1% of the variance in the laterality index of task-based fMRI could be predicted from the fALFF of resting-state fMRI. The present study demonstrates that fALFF can be used as an alternative to task-based fMRI for assessing language laterality. There was a strong positive correlation between the fALFF of the Broca area of resting-state fMRI with the laterality index of task-based fMRI. Furthermore, we demonstrated the efficacy of fALFF for predicting the laterality of task-based fMRI. © 2017 by American Journal of Neuroradiology.

Optimized design and analysis of sparse-sampling FMRI experiments.

PubMed

Perrachione, Tyler K; Ghosh, Satrajit S

2013-01-01

Sparse-sampling is an important methodological advance in functional magnetic resonance imaging (fMRI), in which silent delays are introduced between MR volume acquisitions, allowing for the presentation of auditory stimuli without contamination by acoustic scanner noise and for overt vocal responses without motion-induced artifacts in the functional time series. As such, the sparse-sampling technique has become a mainstay of principled fMRI research into the cognitive and systems neuroscience of speech, language, hearing, and music. Despite being in use for over a decade, there has been little systematic investigation of the acquisition parameters, experimental design considerations, and statistical analysis approaches that bear on the results and interpretation of sparse-sampling fMRI experiments. In this report, we examined how design and analysis choices related to the duration of repetition time (TR) delay (an acquisition parameter), stimulation rate (an experimental design parameter), and model basis function (an analysis parameter) act independently and interactively to affect the neural activation profiles observed in fMRI. First, we conducted a series of computational simulations to explore the parameter space of sparse design and analysis with respect to these variables; second, we validated the results of these simulations in a series of sparse-sampling fMRI experiments. Overall, these experiments suggest the employment of three methodological approaches that can, in many situations, substantially improve the detection of neurophysiological response in sparse fMRI: (1) Sparse analyses should utilize a physiologically informed model that incorporates hemodynamic response convolution to reduce model error. (2) The design of sparse fMRI experiments should maintain a high rate of stimulus presentation to maximize effect size. (3) TR delays of short to intermediate length can be used between acquisitions of sparse-sampled functional image volumes to increase the number of samples and improve statistical power.

Creating 3D visualizations of MRI data: A brief guide.

PubMed

Madan, Christopher R

2015-01-01

While magnetic resonance imaging (MRI) data is itself 3D, it is often difficult to adequately present the results papers and slides in 3D. As a result, findings of MRI studies are often presented in 2D instead. A solution is to create figures that include perspective and can convey 3D information; such figures can sometimes be produced by standard functional magnetic resonance imaging (fMRI) analysis packages and related specialty programs. However, many options cannot provide functionality such as visualizing activation clusters that are both cortical and subcortical (i.e., a 3D glass brain), the production of several statistical maps with an identical perspective in the 3D rendering, or animated renderings. Here I detail an approach for creating 3D visualizations of MRI data that satisfies all of these criteria. Though a 3D 'glass brain' rendering can sometimes be difficult to interpret, they are useful in showing a more overall representation of the results, whereas the traditional slices show a more local view. Combined, presenting both 2D and 3D representations of MR images can provide a more comprehensive view of the study's findings.

Creating 3D visualizations of MRI data: A brief guide

PubMed Central

Madan, Christopher R.

2015-01-01

While magnetic resonance imaging (MRI) data is itself 3D, it is often difficult to adequately present the results papers and slides in 3D. As a result, findings of MRI studies are often presented in 2D instead. A solution is to create figures that include perspective and can convey 3D information; such figures can sometimes be produced by standard functional magnetic resonance imaging (fMRI) analysis packages and related specialty programs. However, many options cannot provide functionality such as visualizing activation clusters that are both cortical and subcortical (i.e., a 3D glass brain), the production of several statistical maps with an identical perspective in the 3D rendering, or animated renderings. Here I detail an approach for creating 3D visualizations of MRI data that satisfies all of these criteria. Though a 3D ‘glass brain’ rendering can sometimes be difficult to interpret, they are useful in showing a more overall representation of the results, whereas the traditional slices show a more local view. Combined, presenting both 2D and 3D representations of MR images can provide a more comprehensive view of the study’s findings. PMID:26594340

A stress MRI of the shoulder for evaluation of ligamentous stabilizers in acute and chronic acromioclavicular joint instabilities.

PubMed

Izadpanah, Kaywan; Winterer, Jan; Vicari, Marco; Jaeger, Martin; Maier, Dirk; Eisebraun, Leonie; Ute Will, Jutta; Kotter, Elmar; Langer, Mathias; Südkamp, Norbert P; Hennig, Jürgen; Weigel, Mathias

2013-06-01

To show the feasibility of a stress magnetic resonance imaging (MRI) as a new method for simultaneous evaluation of the morphology and the functional integrity of the acromioclavicular joint (ACJ) ligamentous stabilizers. MRI of four volunteers, 10 patients with acute, and six with chronic ACJ injuries was performed using a 0.25 T open MRI scanner. A 2D-proton-density and a 3D-gradient-echo sequence at rest and under 6.5 kg shoulder traction were performed. Comparative measurements of the coracoclavicular and the acromioclavicular distance were performed. Additionally, the conoid and trapezoid ligament lengths were measured with multiplanar reconstructions. MRI at rest correctly identified tears of the coracoclavicular and the acromioclavicular ligaments in eight patients suffering acute ACJ injuries. Stress application helped to distinguish between partial and complete coracoclavicular ligament tears in two cases. Insufficiency of the ACJ ligaments was present in all acute and chronic ACJ injuries. Stress application in chronic ACJ ligaments revealed isolated insufficiency of the conoid ligament in three cases and of the trapezoid ligament in one case. Combined insufficiency was present in two cases. Stress MRI facilitates simultaneous acquisition of morphologic and functional information of the ACJ stabilizers. In acute ACJ injuries it helps to distinguish between partial and complete ligament tears. In chronic ACJ injuries it provides functional information of the ligament regrinds. Copyright © 2012 Wiley Periodicals, Inc.

Anticipatory stress associated with functional magnetic resonance imaging: Implications for psychosocial stress research.

PubMed

Gossett, Ethan W; Wheelock, Muriah D; Goodman, Adam M; Orem, Tyler R; Harnett, Nathaniel G; Wood, Kimberly H; Mrug, Sylvie; Granger, Douglas A; Knight, David C

2018-03-01

Stress tasks performed during functional magnetic resonance imaging (fMRI) elicit a relatively small cortisol response compared to stress tasks completed in a traditional behavioral laboratory, which may be due to apprehension of fMRI that elicits an anticipatory stress response. The present study investigated whether anticipatory stress is greater prior to research completed in an MRI environment than in a traditional behavioral laboratory. Anticipatory stress (indexed by cortisol) was greater prior to testing in the MRI environment than traditional behavioral laboratory. Furthermore, anticipation of fMRI elicited a cortisol response commensurate with the response to the stress task in the behavioral laboratory. However, in the MRI environment, post-stress cortisol was significantly lower than baseline cortisol. Taken together, these findings suggest the stress elicited by anticipation of fMRI may lead to acute elevations in cortisol prior to scanning, which may in turn disrupt the cortisol response to stress tasks performed during scanning. Copyright © 2018 Elsevier B.V. All rights reserved.

Role of eNOS in water exchange index maintenance-MRI studies

NASA Astrophysics Data System (ADS)

Atochin, D.; Litvak, M.; Huang, S.; Kim, Y. R.; Huang, P.

2017-08-01

Stroke studies employ experimental models of cerebral ischemic and reperfusion injury in rodents. MRI provides valuable supravital data of cerebral blood flow and brain tissue damage. This paper presents MRI applications for cerebral blood flow research in mice lines with impaired nitric oxide production by endothelial nitric oxide synthase. Our data demonstrates that specific modifications of MRI methodology in transgenic mouse models help to evaluate the role of eNOS in the brain-blood barrier function.

Longitudinal Changes of Resting-State Functional Connectivity during Motor Recovery after Stroke

PubMed Central

Park, Chang-hyun; Chang, Won Hyuk; Ohn, Suk Hoon; Kim, Sung Tae; Bang, Oh Young; Pascual-Leone, Alvaro; Kim, Yun-Hee

2013-01-01

Background and Purpose Functional magnetic resonance imaging (fMRI) studies could provide crucial information on the neural mechanisms of motor recovery in stroke patients. Resting-state fMRI is applicable to stroke patients who are not capable of proper performance of the motor task. In this study, we explored neural correlates of motor recovery in stroke patients by investigating longitudinal changes in resting-state functional connectivity of the ipsilesional primary motor cortex (M1). Methods A longitudinal observational study using repeated fMRI experiments was conducted in 12 patients with stroke. Resting-state fMRI data were acquired four times over a period of 6 months. Patients participated in the first session of fMRI shortly after onset, and thereafter in subsequent sessions at 1, 3, and 6 months after onset. Resting-state functional connectivity of the ipsilesional M1 was assessed and compared with that of healthy subjects. Results Compared with healthy subjects, patients demonstrated higher functional connectivity with the ipsilesional frontal and parietal cortices, bilateral thalamus, and cerebellum. Instead, functional connectivity with the contralesional M1 and occipital cortex were decreased in stroke patients. Functional connectivity between the ipsilesional and contralesional M1 showed the most asymmetry at 1 month after onset to the ipsilesional side. Functional connectivity of the ipsilesional M1 with the contralesional thalamus, supplementary motor area, and middle frontal gyrus at onset was positively correlated with motor recovery at 6 months after stroke. Conclusions Resting-state fMRI elicited distinctive but comparable results with previous task-based fMRI, presenting complementary and practical values for use in the study of stroke patients. PMID:21441147

Real-time fMRI neurofeedback to down-regulate superior temporal gyrus activity in patients with schizophrenia and auditory hallucinations: a proof-of-concept study.

PubMed

Orlov, Natasza D; Giampietro, Vincent; O'Daly, Owen; Lam, Sheut-Ling; Barker, Gareth J; Rubia, Katya; McGuire, Philip; Shergill, Sukhwinder S; Allen, Paul

2018-02-12

Neurocognitive models and previous neuroimaging work posit that auditory verbal hallucinations (AVH) arise due to increased activity in speech-sensitive regions of the left posterior superior temporal gyrus (STG). Here, we examined if patients with schizophrenia (SCZ) and AVH could be trained to down-regulate STG activity using real-time functional magnetic resonance imaging neurofeedback (rtfMRI-NF). We also examined the effects of rtfMRI-NF training on functional connectivity between the STG and other speech and language regions. Twelve patients with SCZ and treatment-refractory AVH were recruited to participate in the study and were trained to down-regulate STG activity using rtfMRI-NF, over four MRI scanner visits during a 2-week training period. STG activity and functional connectivity were compared pre- and post-training. Patients successfully learnt to down-regulate activity in their left STG over the rtfMRI-NF training. Post- training, patients showed increased functional connectivity between the left STG, the left inferior prefrontal gyrus (IFG) and the inferior parietal gyrus. The post-training increase in functional connectivity between the left STG and IFG was associated with a reduction in AVH symptoms over the training period. The speech-sensitive region of the left STG is a suitable target region for rtfMRI-NF in patients with SCZ and treatment-refractory AVH. Successful down-regulation of left STG activity can increase functional connectivity between speech motor and perception regions. These findings suggest that patients with AVH have the ability to alter activity and connectivity in speech and language regions, and raise the possibility that rtfMRI-NF training could present a novel therapeutic intervention in SCZ.

Joint brain connectivity estimation from diffusion and functional MRI data

NASA Astrophysics Data System (ADS)

Chu, Shu-Hsien; Lenglet, Christophe; Parhi, Keshab K.

2015-03-01

Estimating brain wiring patterns is critical to better understand the brain organization and function. Anatomical brain connectivity models axonal pathways, while the functional brain connectivity characterizes the statistical dependencies and correlation between the activities of various brain regions. The synchronization of brain activity can be inferred through the variation of blood-oxygen-level dependent (BOLD) signal from functional MRI (fMRI) and the neural connections can be estimated using tractography from diffusion MRI (dMRI). Functional connections between brain regions are supported by anatomical connections, and the synchronization of brain activities arises through sharing of information in the form of electro-chemical signals on axon pathways. Jointly modeling fMRI and dMRI data may improve the accuracy in constructing anatomical connectivity as well as functional connectivity. Such an approach may lead to novel multimodal biomarkers potentially able to better capture functional and anatomical connectivity variations. We present a novel brain network model which jointly models the dMRI and fMRI data to improve the anatomical connectivity estimation and extract the anatomical subnetworks associated with specific functional modes by constraining the anatomical connections as structural supports to the functional connections. The key idea is similar to a multi-commodity flow optimization problem that minimizes the cost or maximizes the efficiency for flow configuration and simultaneously fulfills the supply-demand constraint for each commodity. In the proposed network, the nodes represent the grey matter (GM) regions providing brain functionality, and the links represent white matter (WM) fiber bundles connecting those regions and delivering information. The commodities can be thought of as the information corresponding to brain activity patterns as obtained for instance by independent component analysis (ICA) of fMRI data. The concept of information flow is introduced and used to model the propagation of information between GM areas through WM fiber bundles. The link capacity, i.e., ability to transfer information, is characterized by the relative strength of fiber bundles, e.g., fiber count gathered from the tractography of dMRI data. The node information demand is considered to be proportional to the correlation between neural activity at various cortical areas involved in a particular functional mode (e.g. visual, motor, etc.). These two properties lead to the link capacity and node demand constraints in the proposed model. Moreover, the information flow of a link cannot exceed the demand from either end node. This is captured by the feasibility constraints. Two different cost functions are considered in the optimization formulation in this paper. The first cost function, the reciprocal of fiber strength represents the unit cost for information passing through the link. In the second cost function, a min-max (minimizing the maximal link load) approach is used to balance the usage of each link. Optimizing the first cost function selects the pathway with strongest fiber strength for information propagation. In the second case, the optimization procedure finds all the possible propagation pathways and allocates the flow proportionally to their strength. Additionally, a penalty term is incorporated with both the cost functions to capture the possible missing and weak anatomical connections. With this set of constraints and the proposed cost functions, solving the network optimization problem recovers missing and weak anatomical connections supported by the functional information and provides the functional-associated anatomical subnetworks. Feasibility is demonstrated using realistic diffusion and functional MRI phantom data. It is shown that the proposed model recovers the maximum number of true connections, with fewest number of false connections when compared with the connectivity derived from a joint probabilistic model using the expectation-maximization (EM) algorithm presented in a prior work. We also apply the proposed method to data provided by the Human Connectome Project (HCP).

MRI in multiple sclerosis: current status and future prospects

PubMed Central

Bakshi, Rohit; Thompson, Alan J; Rocca, Maria A; Pelletier, Daniel; Dousset, Vincent; Barkhof, Frederik; Inglese, Matilde; Guttmann, Charles R G; Horsfield, Mark A; Filippi, Massimo

2008-01-01

Many promising MRI approaches for research or clinical management of multiple sclerosis (MS) have recently emerged, or are under development or refinement. Advanced MRI methods need to be assessed to determine whether they allow earlier diagnosis or better identification of phenotypes. Improved post-processing should allow more efficient and complete extraction of information from images. Magnetic resonance spectroscopy should improve in sensitivity and specificity with higher field strengths and should enable the detection of a wider array of metabolites. Diffusion imaging is moving closer to the goal of defining structural connectivity and, thereby, determining the functional significance of lesions at specific locations. Cell-specific imaging now seems feasible with new magnetic resonance contrast agents. The imaging of myelin water fraction brings the hope of providing a specific measure of myelin content. Ultra-high-field MRI increases sensitivity, but also presents new technical challenges. Here, we review these recent developments in MRI for MS, and also look forward to refinements in spinal-cord imaging, optic-nerve imaging, perfusion MRI, and functional MRI. Advances in MRI should improve our ability to diagnose, monitor, and understand the pathophysiology of MS. PMID:18565455

Data-driven analysis of functional brain interactions during free listening to music and speech.

PubMed

Fang, Jun; Hu, Xintao; Han, Junwei; Jiang, Xi; Zhu, Dajiang; Guo, Lei; Liu, Tianming

2015-06-01

Natural stimulus functional magnetic resonance imaging (N-fMRI) such as fMRI acquired when participants were watching video streams or listening to audio streams has been increasingly used to investigate functional mechanisms of the human brain in recent years. One of the fundamental challenges in functional brain mapping based on N-fMRI is to model the brain's functional responses to continuous, naturalistic and dynamic natural stimuli. To address this challenge, in this paper we present a data-driven approach to exploring functional interactions in the human brain during free listening to music and speech streams. Specifically, we model the brain responses using N-fMRI by measuring the functional interactions on large-scale brain networks with intrinsically established structural correspondence, and perform music and speech classification tasks to guide the systematic identification of consistent and discriminative functional interactions when multiple subjects were listening music and speech in multiple categories. The underlying premise is that the functional interactions derived from N-fMRI data of multiple subjects should exhibit both consistency and discriminability. Our experimental results show that a variety of brain systems including attention, memory, auditory/language, emotion, and action networks are among the most relevant brain systems involved in classic music, pop music and speech differentiation. Our study provides an alternative approach to investigating the human brain's mechanism in comprehension of complex natural music and speech.

Resting-state functional magnetic resonance imaging for surgical planning in pediatric patients: a preliminary experience.

PubMed

Roland, Jarod L; Griffin, Natalie; Hacker, Carl D; Vellimana, Ananth K; Akbari, S Hassan; Shimony, Joshua S; Smyth, Matthew D; Leuthardt, Eric C; Limbrick, David D

2017-12-01

OBJECTIVE Cerebral mapping for surgical planning and operative guidance is a challenging task in neurosurgery. Pediatric patients are often poor candidates for many modern mapping techniques because of inability to cooperate due to their immature age, cognitive deficits, or other factors. Resting-state functional MRI (rs-fMRI) is uniquely suited to benefit pediatric patients because it is inherently noninvasive and does not require task performance or significant cooperation. Recent advances in the field have made mapping cerebral networks possible on an individual basis for use in clinical decision making. The authors present their initial experience translating rs-fMRI into clinical practice for surgical planning in pediatric patients. METHODS The authors retrospectively reviewed cases in which the rs-fMRI analysis technique was used prior to craniotomy in pediatric patients undergoing surgery in their institution. Resting-state analysis was performed using a previously trained machine-learning algorithm for identification of resting-state networks on an individual basis. Network maps were uploaded to the clinical imaging and surgical navigation systems. Patient demographic and clinical characteristics, including need for sedation during imaging and use of task-based fMRI, were also recorded. RESULTS Twenty patients underwent rs-fMRI prior to craniotomy between December 2013 and June 2016. Their ages ranged from 1.9 to 18.4 years, and 12 were male. Five of the 20 patients also underwent task-based fMRI and one underwent awake craniotomy. Six patients required sedation to tolerate MRI acquisition, including resting-state sequences. Exemplar cases are presented including anatomical and resting-state functional imaging. CONCLUSIONS Resting-state fMRI is a rapidly advancing field of study allowing for whole brain analysis by a noninvasive modality. It is applicable to a wide range of patients and effective even under general anesthesia. The nature of resting-state analysis precludes any need for task cooperation. These features make rs-fMRI an ideal technology for cerebral mapping in pediatric neurosurgical patients. This review of the use of rs-fMRI mapping in an initial pediatric case series demonstrates the feasibility of utilizing this technique in pediatric neurosurgical patients. The preliminary experience presented here is a first step in translating this technique to a broader clinical practice.

Dissociated language functions: a matter of atypical language lateralization or cerebral plasticity?

PubMed

Acioly, Marcus Andre; Gharabaghi, Alireza; Zimmermann, Christoph; Erb, Michael; Heckl, Stefan; Tatagiba, Marcos

2014-01-01

The left hemisphere is generally considered to harbor language functions. Atypical cortical language lateralization is mainly demonstrated in left-handed and ambidextrous individuals, whereas dissociated language functions have been reported in association with brain injuries as a part of the reorganization process. We present a thoughtful discussion on the underlying mechanisms of dissociated language functions through an illustrative case of dissociated expressive language. A 31-year-old left-handed woman presented with a recurrent left frontal glioma. Preoperative language functional magnetic resonance imaging (fMRI) panel revealed right-sided dominance for two different language tasks (verbal fluency and visual naming), and the word chain task demonstrated maximal activation in the left hemisphere at the posterior margin of the tumor. The patient was operated on awake to assess language functions intraoperatively. Preoperative fMRI findings were confirmed revealing a task-specific dissociation of expressive language functions. Surgical resection was taken to the functional boundaries. Postoperatively, no language dysfunction occurred. Dissociated language functions are prone to occur in long-standing lesions. Different patterns of dissociation may be encountered due to interindividual particularities and cerebral plasticity. The presented patient is unique by demonstrating new insight into expressive language dissociation, emphasizing the role of a preoperative language fMRI panel and the capability of intraoperative language mapping for identifying special language networks. Georg Thieme Verlag KG Stuttgart · New York.

Neuropsychological assessment of language functions during functional magnetic resonance imaging: development of new tasks. Preliminary report.

PubMed

Fersten, Ewa; Jakuciński, Maciej; Kuliński, Radosław; Koziara, Henryk; Mroziak, Barbara; Nauman, Paweł

2011-01-01

Due to the complex and extended cerebral organization of language functions, the brain regions crucial for speech and language, i.e. eloquent areas, have to be affected by neurooncological surgery. One of the techniques that may be helpful in pre-operative planning of the extent of tumour removal and estimating possible complications seems to be functional magnetic resonance imaging (fMRI). The aim of the study was to develop valid procedures for neuropsychological assessment of various language functions visualisable by fMRI in healthy individuals. In this fMRI study, 10 healthy (with no CNS pathology), right-handed volunteers aged 25-35 were examined using four tasks designed to measure different language functions, and one for short-term memory assessment. A 1.5-T MRI scanner performing ultrafast functional (EPI) sequences with 4-mm slice thickness and 1-mm interslice gap was used to detect the BOLD response to stimuli present-ed in a block design (30-second alternating blocks of activity and rest). The analyses used the SPM software running in a MATLAB environment, and the obtained data were interpreted by means of colour-coded maps superimposed on structural brain scans. For each of the tasks developed for particular language functions, a different area of increased neuronal activity was found. The differential localization of function-related neuronal activity seems interesting and the research worth continuing, since verbal communication failure may result from impairment of any of various language functions, and studies reported in the literature seem to focus on verbal expression only.

Update on the MRI Core of the Alzheimer's Disease Neuroimaging Initiative

PubMed Central

Jack, Clifford R; Bernstein, Matt A; Borowski, Bret J; Gunter, Jeffrey L; Fox, Nick C; Thompson, Paul M; Schuff, Norbert; Krueger, Gunnar; Killiany, Ronald J; DeCarli, Charles S; Dale, Anders M; Weiner, Michael W

2010-01-01

Functions of the ADNI MRI core fall into three categories: (1) those of the central MRI core lab at Mayo Clinic, Rochester, Minnesota, needed to generate high quality MRI data in all subjects at each time point; (2) those of the funded ADNI MRI core imaging analysis groups responsible for analyzing the MRI data, and (3) the joint function of the entire MRI core in designing and problem solving MR image acquisition, pre-processing and analyses methods. The primary objective of ADNI was and continues to be improving methods for clinical trials in Alzheimer's disease. Our approach to the present (“ADNI-GO”) and future (“ADNI-2”, if funded) MRI protocol will be to maintain MRI methodological consistency in previously enrolled “ADNI-1” subjects who are followed longitudinally in ADNI-GO and ADNI-2. We will modernize and expand the MRI protocol for all newly enrolled ADNI-GO and ADNI-2 subjects. All newly enrolled subjects will be scanned at 3T with a core set of three sequence types: 3D T1-weighted volume, FLAIR, and a long TE gradient echo volumetric acquisition for micro hemorrhage detection. In addition to this core ADNI-GO and ADNI-2 protocol, we will perform vendor specific pilot sub-studies of arterial spin labeling perfusion, resting state functional connectivity and diffusion tensor imaging. One each of these sequences will be added to the core protocol on systems from each MRI vendor. These experimental sub-studies are designed to demonstrate the feasibility of acquiring useful data in a multi-center (but single vendor) setting for these three emerging MRI applications. PMID:20451869

Methods of the pharmacological imaging of the cannabinoid system (PhICS) study: towards understanding the role of the brain endocannabinoid system in human cognition.

PubMed

van Hell, Hendrika H; Bossong, Matthijs G; Jager, Gerry; Kahn, René S; Ramsey, Nick F

2011-03-01

Various lines of (pre)clinical research indicate that cannabinoid agents carry the potential for therapeutic application to reduce symptoms in several psychiatric disorders. However, direct testing of the involvement of cannabinoid brain systems in psychiatric syndromes is essential for further development. In the Pharmacological Imaging of the Cannabinoid System (PhICS) study, the involvement of the endocannabinoid system in cognitive brain function is assessed by comparing acute effects of the cannabinoid agonist Δ9-tetrahydrocannabinol (THC) on brain function between healthy controls and groups of psychiatric patients showing cognitive dysfunction. This article describes the objectives and methods of the PhICS study and presents preliminary results of the administration procedure on subjective and neurophysiological parameters. Core elements in the methodology of PhICS are the administration method (THC is administered by inhalation using a vaporizing device) and a comprehensive use of pharmacological magnetic resonance imaging (phMRI) combining several types of MRI scans including functional MRI (fMRI), Arterial Spin Labeling (ASL) to measure brain perfusion, and resting-state fMRI. Additional methods like neuropsychological testing further specify the exact role of the endocannabinoid system in regulating cognition. Preliminary results presented in this paper indicate robust behavioral and subjective effects of THC. In addition, fMRI paradigms demonstrate activation of expected networks of brain regions in the cognitive domains of interest. The presented administration and assessment protocol provides a basis for further research on the involvement of the endocannabionoid systems in behavior and in psychopathology, which in turn may lead to development of therapeutic opportunities of cannabinoid ligands. Copyright © 2011 John Wiley & Sons, Ltd.

A guide to using functional magnetic resonance imaging to study Alzheimer's disease in animal models.

PubMed

Asaad, Mazen; Lee, Jin Hyung

2018-05-18

Alzheimer's disease is a leading healthcare challenge facing our society today. Functional magnetic resonance imaging (fMRI) of the brain has played an important role in our efforts to understand how Alzheimer's disease alters brain function. Using fMRI in animal models of Alzheimer's disease has the potential to provide us with a more comprehensive understanding of the observations made in human clinical fMRI studies. However, using fMRI in animal models of Alzheimer's disease presents some unique challenges. Here, we highlight some of these challenges and discuss potential solutions for researchers interested in performing fMRI in animal models. First, we briefly summarize our current understanding of Alzheimer's disease from a mechanistic standpoint. We then overview the wide array of animal models available for studying this disease and how to choose the most appropriate model to study, depending on which aspects of the condition researchers seek to investigate. Finally, we discuss the contributions of fMRI to our understanding of Alzheimer's disease and the issues to consider when designing fMRI studies for animal models, such as differences in brain activity based on anesthetic choice and ways to interrogate more specific questions in rodents beyond those that can be addressed in humans. The goal of this article is to provide information on the utility of fMRI, and approaches to consider when using fMRI, for studies of Alzheimer's disease in animal models. © 2018. Published by The Company of Biologists Ltd.

A guide to using functional magnetic resonance imaging to study Alzheimer's disease in animal models

PubMed Central

Asaad, Mazen

2018-01-01

ABSTRACT Alzheimer's disease is a leading healthcare challenge facing our society today. Functional magnetic resonance imaging (fMRI) of the brain has played an important role in our efforts to understand how Alzheimer's disease alters brain function. Using fMRI in animal models of Alzheimer's disease has the potential to provide us with a more comprehensive understanding of the observations made in human clinical fMRI studies. However, using fMRI in animal models of Alzheimer's disease presents some unique challenges. Here, we highlight some of these challenges and discuss potential solutions for researchers interested in performing fMRI in animal models. First, we briefly summarize our current understanding of Alzheimer's disease from a mechanistic standpoint. We then overview the wide array of animal models available for studying this disease and how to choose the most appropriate model to study, depending on which aspects of the condition researchers seek to investigate. Finally, we discuss the contributions of fMRI to our understanding of Alzheimer's disease and the issues to consider when designing fMRI studies for animal models, such as differences in brain activity based on anesthetic choice and ways to interrogate more specific questions in rodents beyond those that can be addressed in humans. The goal of this article is to provide information on the utility of fMRI, and approaches to consider when using fMRI, for studies of Alzheimer's disease in animal models. PMID:29784664

Characterizing Response to Elemental Unit of Acoustic Imaging Noise: An fMRI Study

PubMed Central

Luh, Wen-Ming; Talavage, Thomas M.

2010-01-01

Acoustic imaging noise produced during functional magnetic resonance imaging (fMRI) studies can hinder auditory fMRI research analysis by altering the properties of the acquired time-series data. Acoustic imaging noise can be especially confounding when estimating the time course of the hemodynamic response (HDR) in auditory event-related fMRI (fMRI) experiments. This study is motivated by the desire to establish a baseline function that can serve not only as a comparison to other quantities of acoustic imaging noise for determining how detrimental is one's experimental noise, but also as a foundation for a model that compensates for the response to acoustic imaging noise. Therefore, the amplitude and spatial extent of the HDR to the elemental unit of acoustic imaging noise (i.e., a single ping) associated with echoplanar acquisition were characterized and modeled. Results from this fMRI study at 1.5 T indicate that the group-averaged HDR in left and right auditory cortex to acoustic imaging noise (duration of 46 ms) has an estimated peak magnitude of 0.29% (right) to 0.48% (left) signal change from baseline, peaks between 3 and 5 s after stimulus presentation, and returns to baseline and remains within the noise range approximately 8 s after stimulus presentation. PMID:19304477

Characterization of functional brain activity and connectivity using EEG and fMRI in patients with sickle cell disease.

PubMed

Case, Michelle; Zhang, Huishi; Mundahl, John; Datta, Yvonne; Nelson, Stephen; Gupta, Kalpna; He, Bin

2017-01-01

Sickle cell disease (SCD) is a red blood cell disorder that causes many complications including life-long pain. Treatment of pain remains challenging due to a poor understanding of the mechanisms and limitations to characterize and quantify pain. In the present study, we examined simultaneously recording functional MRI (fMRI) and electroencephalogram (EEG) to better understand neural connectivity as a consequence of chronic pain in SCD patients. We performed independent component analysis and seed-based connectivity on fMRI data. Spontaneous power and microstate analysis was performed on EEG-fMRI data. ICA analysis showed that patients lacked activity in the default mode network (DMN) and executive control network compared to controls. EEG-fMRI data revealed that the insula cortex's role in salience increases with age in patients. EEG microstate analysis showed patients had increased activity in pain processing regions. The cerebellum in patients showed a stronger connection to the periaqueductal gray matter (involved in pain inhibition), and negative connections to pain processing areas. These results suggest that patients have reduced activity of DMN and increased activity in pain processing regions during rest. The present findings suggest resting state connectivity differences between patients and controls can be used as novel biomarkers of SCD pain.

Visual cortex in dementia with Lewy bodies: magnetic resonance imaging study

PubMed Central

Taylor, John-Paul; Firbank, Michael J.; He, Jiabao; Barnett, Nicola; Pearce, Sarah; Livingstone, Anthea; Vuong, Quoc; McKeith, Ian G.; O’Brien, John T.

2012-01-01

Background Visual hallucinations and visuoperceptual deficits are common in dementia with Lewy bodies, suggesting that cortical visual function may be abnormal. Aims To investigate: (1) cortical visual function using functional magnetic resonance imaging (fMRI); and (2) the nature and severity of perfusion deficits in visual areas using arterial spin labelling (ASL)-MRI. Method In total, 17 participants with dementia with Lewy bodies (DLB group) and 19 similarly aged controls were presented with simple visual stimuli (checkerboard, moving dots, and objects) during fMRI and subsequently underwent ASL-MRI (DLB group n = 15, control group n = 19). Results Functional activations were evident in visual areas in both the DLB and control groups in response to checkerboard and objects stimuli but reduced visual area V5/MT (middle temporal) activation occurred in the DLB group in response to motion stimuli. Posterior cortical perfusion deficits occurred in the DLB group, particularly in higher visual areas. Conclusions Higher visual areas, particularly occipito-parietal, appear abnormal in dementia with Lewy bodies, while there is a preservation of function in lower visual areas (V1 and V2/3). PMID:22500014

A test-retest dataset for assessing long-term reliability of brain morphology and resting-state brain activity.

PubMed

Huang, Lijie; Huang, Taicheng; Zhen, Zonglei; Liu, Jia

2016-03-15

We present a test-retest dataset for evaluation of long-term reliability of measures from structural and resting-state functional magnetic resonance imaging (sMRI and rfMRI) scans. The repeated scan dataset was collected from 61 healthy adults in two sessions using highly similar imaging parameters at an interval of 103-189 days. However, as the imaging parameters were not completely identical, the reliability estimated from this dataset shall reflect the lower bounds of the true reliability of sMRI/rfMRI measures. Furthermore, in conjunction with other test-retest datasets, our dataset may help explore the impact of different imaging parameters on reliability of sMRI/rfMRI measures, which is especially critical for assessing datasets collected from multiple centers. In addition, intelligence quotient (IQ) was measured for each participant using Raven's Advanced Progressive Matrices. The data can thus be used for purposes other than assessing reliability of sMRI/rfMRI alone. For example, data from each single session could be used to associate structural and functional measures of the brain with the IQ metrics to explore brain-IQ association.

Update on the magnetic resonance imaging core of the Alzheimer's disease neuroimaging initiative.

PubMed

Jack, Clifford R; Bernstein, Matt A; Borowski, Bret J; Gunter, Jeffrey L; Fox, Nick C; Thompson, Paul M; Schuff, Norbert; Krueger, Gunnar; Killiany, Ronald J; Decarli, Charles S; Dale, Anders M; Carmichael, Owen W; Tosun, Duygu; Weiner, Michael W

2010-05-01

Functions of the Alzheimer's Disease Neuroimaging Initiative (ADNI) magnetic resonance imaging (MRI) core fall into three categories: (1) those of the central MRI core laboratory at Mayo Clinic, Rochester, Minnesota, needed to generate high quality MRI data in all subjects at each time point; (2) those of the funded ADNI MRI core imaging analysis groups responsible for analyzing the MRI data; and (3) the joint function of the entire MRI core in designing and problem solving MR image acquisition, pre-processing, and analyses methods. The primary objective of ADNI was and continues to be improving methods for clinical trials in Alzheimer's disease. Our approach to the present ("ADNI-GO") and future ("ADNI-2," if funded) MRI protocol will be to maintain MRI methodological consistency in the previously enrolled "ADNI-1" subjects who are followed up longitudinally in ADNI-GO and ADNI-2. We will modernize and expand the MRI protocol for all newly enrolled ADNI-GO and ADNI-2 subjects. All newly enrolled subjects will be scanned at 3T with a core set of three sequence types: 3D T1-weighted volume, FLAIR, and a long TE gradient echo volumetric acquisition for micro hemorrhage detection. In addition to this core ADNI-GO and ADNI-2 protocol, we will perform vendor-specific pilot sub-studies of arterial spin-labeling perfusion, resting state functional connectivity, and diffusion tensor imaging. One of these sequences will be added to the core protocol on systems from each MRI vendor. These experimental sub-studies are designed to demonstrate the feasibility of acquiring useful data in a multicenter (but single vendor) setting for these three emerging MRI applications. Copyright 2010 The Alzheimer

Multimodal description of whole brain connectivity: A comparison of resting state MEG, fMRI, and DWI.

PubMed

Garcés, Pilar; Pereda, Ernesto; Hernández-Tamames, Juan A; Del-Pozo, Francisco; Maestú, Fernando; Pineda-Pardo, José Ángel

2016-01-01

Structural and functional connectivity (SC and FC) have received much attention over the last decade, as they offer unique insight into the coordination of brain functioning. They are often assessed independently with three imaging modalities: SC using diffusion-weighted imaging (DWI), FC using functional magnetic resonance imaging (fMRI), and magnetoencephalography/electroencephalography (MEG/EEG). DWI provides information about white matter organization, allowing the reconstruction of fiber bundles. fMRI uses blood-oxygenation level-dependent (BOLD) contrast to indirectly map neuronal activation. MEG and EEG are direct measures of neuronal activity, as they are sensitive to the synchronous inputs in pyramidal neurons. Seminal studies have targeted either the electrophysiological substrate of BOLD or the anatomical basis of FC. However, multimodal comparisons have been scarcely performed, and the relation between SC, fMRI-FC, and MEG-FC is still unclear. Here we present a systematic comparison of SC, resting state fMRI-FC, and MEG-FC between cortical regions, by evaluating their similarities at three different scales: global network, node, and hub distribution. We obtained strong similarities between the three modalities, especially for the following pairwise combinations: SC and fMRI-FC; SC and MEG-FC at theta, alpha, beta and gamma bands; and fMRI-FC and MEG-FC in alpha and beta. Furthermore, highest node similarity was found for regions of the default mode network and primary motor cortex, which also presented the highest hubness score. Distance was partially responsible for these similarities since it biased all three connectivity estimates, but not the unique contributor, since similarities remained after controlling for distance. © 2015 Wiley Periodicals, Inc.

Joint Segmentation of Anatomical and Functional Images: Applications in Quantification of Lesions from PET, PET-CT, MRI-PET, and MRI-PET-CT Images

PubMed Central

Bagci, Ulas; Udupa, Jayaram K.; Mendhiratta, Neil; Foster, Brent; Xu, Ziyue; Yao, Jianhua; Chen, Xinjian; Mollura, Daniel J.

2013-01-01

We present a novel method for the joint segmentation of anatomical and functional images. Our proposed methodology unifies the domains of anatomical and functional images, represents them in a product lattice, and performs simultaneous delineation of regions based on random walk image segmentation. Furthermore, we also propose a simple yet effective object/background seed localization method to make the proposed segmentation process fully automatic. Our study uses PET, PET-CT, MRI-PET, and fused MRI-PET-CT scans (77 studies in all) from 56 patients who had various lesions in different body regions. We validated the effectiveness of the proposed method on different PET phantoms as well as on clinical images with respect to the ground truth segmentation provided by clinicians. Experimental results indicate that the presented method is superior to threshold and Bayesian methods commonly used in PET image segmentation, is more accurate and robust compared to the other PET-CT segmentation methods recently published in the literature, and also it is general in the sense of simultaneously segmenting multiple scans in real-time with high accuracy needed in routine clinical use. PMID:23837967

Functional MRI evidence for fine motor praxis dysfunction in children with persistent speech disorders

PubMed Central

Redle, Erin; Vannest, Jennifer; Maloney, Thomas; Tsevat, Rebecca K.; Eikenberry, Sarah; Lewis, Barbara; Shriberg, Lawrence D.; Tkach, Jean; Holland, Scott K.

2014-01-01

Children with persistent speech disorders (PSD) often present with overt or subtle motor deficits; the possibility that speech disorders and motor deficits could arise from a shared neurological base is currently unknown. Functional MRI (fMRI) was used to examine the brain networks supporting fine motor praxis in children with PSD and without clinically identified fine motor deficits. Methods This case-control study included 12 children with PSD (mean age 7.42 years, 4 female) and 12 controls (mean age 7.44 years, 4 female). Children completed behavioral evaluations using standardized motor assessments and parent reported functional measures. During fMRI scanning, participants completed a cued finger tapping task contrasted passive listening. A general linear model approach identified brain regions associated with finger tapping in each group and regions that differed between groups. The relationship between regional fMRI activation and fine motor skill was assessed using a regression analysis. Results Children with PSD had significantly poorer results for rapid speech production and fine motor praxis skills, but did not differ on classroom functional skills. Functional MRI results showed that children with PSD had significantly more activation in the cerebellum during finger tapping. Positive correlations between performance on a fine motor praxis test and activation multiple cortical regions were noted for children with PSD but not for controls. Conclusions Over-activation in the cerebellum during a motor task may reflect a subtle abnormality in the non-speech motor neural circuitry in children with PSD. PMID:25481413

A SVM-based quantitative fMRI method for resting-state functional network detection.

PubMed

Song, Xiaomu; Chen, Nan-kuei

2014-09-01

Resting-state functional magnetic resonance imaging (fMRI) aims to measure baseline neuronal connectivity independent of specific functional tasks and to capture changes in the connectivity due to neurological diseases. Most existing network detection methods rely on a fixed threshold to identify functionally connected voxels under the resting state. Due to fMRI non-stationarity, the threshold cannot adapt to variation of data characteristics across sessions and subjects, and generates unreliable mapping results. In this study, a new method is presented for resting-state fMRI data analysis. Specifically, the resting-state network mapping is formulated as an outlier detection process that is implemented using one-class support vector machine (SVM). The results are refined by using a spatial-feature domain prototype selection method and two-class SVM reclassification. The final decision on each voxel is made by comparing its probabilities of functionally connected and unconnected instead of a threshold. Multiple features for resting-state analysis were extracted and examined using an SVM-based feature selection method, and the most representative features were identified. The proposed method was evaluated using synthetic and experimental fMRI data. A comparison study was also performed with independent component analysis (ICA) and correlation analysis. The experimental results show that the proposed method can provide comparable or better network detection performance than ICA and correlation analysis. The method is potentially applicable to various resting-state quantitative fMRI studies. Copyright © 2014 Elsevier Inc. All rights reserved.

Magnetic Resonance Safety

PubMed Central

Sammet, Steffen

2016-01-01

Magnetic Resonance Imaging (MRI) has a superior soft-tissue contrast compared to other radiological imaging modalities and its physiological and functional applications have led to a significant increase in MRI scans worldwide. A comprehensive MRI safety training to protect patients and other healthcare workers from potential bio-effects and risks of the magnetic fields in an MRI suite is therefore essential. The knowledge of the purpose of safety zones in an MRI suite as well as MRI appropriateness criteria is important for all healthcare professionals who will work in the MRI environment or refer patients for MRI scans. The purpose of this article is to give an overview of current magnetic resonance safety guidelines and discuss the safety risks of magnetic fields in an MRI suite including forces and torque of ferromagnetic objects, tissue heating, peripheral nerve stimulation and hearing damages. MRI safety and compatibility of implanted devices, MRI scans during pregnancy and the potential risks of MRI contrast agents will also be discussed and a comprehensive MRI safety training to avoid fatal accidents in an MRI suite will be presented. PMID:26940331

Genetic and Diagnostic Biomarker Development in ASD Toddlers Using Resting State Functional MRI

DTIC Science & Technology

2016-09-01

networks during resting states. Autism spectrum disorder (ASD) begins prenatal, and early maldevelopment is present in many sites and systems that mediate...molecular and genomic evidence indicates autism spectrum disorder (ASD) begins prenatally, most likely by or before the late second trimester 10-15 as...ages 3 to 4 years. 2. KEYWORDS Autism spectrum disorder, ASD, early brain development, intrinsic functional brain networks, fMRI, infants, toddlers

Age-Related Variability in Cortical Activity during Language Processing

ERIC Educational Resources Information Center

Fridriksson, Julius; Morrow, K. Leigh; Moser, Dana; Baylis, Gordon C.

2006-01-01

Purpose: The present study investigated the extent of cortical activity during overt picture naming using functional magnetic resonance imaging (fMRI). Method: Participants comprised 20 healthy, adult participants with ages ranging from 20 to 82 years. While undergoing fMRI, participants completed a picture-naming task consisting of 60…

Aging effects on functional auditory and visual processing using fMRI with variable sensory loading.

PubMed

Cliff, Michael; Joyce, Dan W; Lamar, Melissa; Dannhauser, Thomas; Tracy, Derek K; Shergill, Sukhwinder S

2013-05-01

Traditionally, studies investigating the functional implications of age-related structural brain alterations have focused on higher cognitive processes; by increasing stimulus load, these studies assess behavioral and neurophysiological performance. In order to understand age-related changes in these higher cognitive processes, it is crucial to examine changes in visual and auditory processes that are the gateways to higher cognitive functions. This study provides evidence for age-related functional decline in visual and auditory processing, and regional alterations in functional brain processing, using non-invasive neuroimaging. Using functional magnetic resonance imaging (fMRI), younger (n=11; mean age=31) and older (n=10; mean age=68) adults were imaged while observing flashing checkerboard images (passive visual stimuli) and hearing word lists (passive auditory stimuli) across varying stimuli presentation rates. Younger adults showed greater overall levels of temporal and occipital cortical activation than older adults for both auditory and visual stimuli. The relative change in activity as a function of stimulus presentation rate showed differences between young and older participants. In visual cortex, the older group showed a decrease in fMRI blood oxygen level dependent (BOLD) signal magnitude as stimulus frequency increased, whereas the younger group showed a linear increase. In auditory cortex, the younger group showed a relative increase as a function of word presentation rate, while older participants showed a relatively stable magnitude of fMRI BOLD response across all rates. When analyzing participants across all ages, only the auditory cortical activation showed a continuous, monotonically decreasing BOLD signal magnitude as a function of age. Our preliminary findings show an age-related decline in demand-related, passive early sensory processing. As stimulus demand increases, visual and auditory cortex do not show increases in activity in older compared to younger people. This may negatively impact on the fidelity of information available to higher cognitive processing. Such evidence may inform future studies focused on cognitive decline in aging. Copyright © 2012 Elsevier Ltd. All rights reserved.

Intensity-Curvature Measurement Approaches for the Diagnosis of Magnetic Resonance Imaging Brain Tumors.

PubMed

Ciulla, Carlo; Veljanovski, Dimitar; Rechkoska Shikoska, Ustijana; Risteski, Filip A

2015-11-01

This research presents signal-image post-processing techniques called Intensity-Curvature Measurement Approaches with application to the diagnosis of human brain tumors detected through Magnetic Resonance Imaging (MRI). Post-processing of the MRI of the human brain encompasses the following model functions: (i) bivariate cubic polynomial, (ii) bivariate cubic Lagrange polynomial, (iii) monovariate sinc, and (iv) bivariate linear. The following Intensity-Curvature Measurement Approaches were used: (i) classic-curvature, (ii) signal resilient to interpolation, (iii) intensity-curvature measure and (iv) intensity-curvature functional. The results revealed that the classic-curvature, the signal resilient to interpolation and the intensity-curvature functional are able to add additional information useful to the diagnosis carried out with MRI. The contribution to the MRI diagnosis of our study are: (i) the enhanced gray level scale of the tumor mass and the well-behaved representation of the tumor provided through the signal resilient to interpolation, and (ii) the visually perceptible third dimension perpendicular to the image plane provided through the classic-curvature and the intensity-curvature functional.

Intensity-Curvature Measurement Approaches for the Diagnosis of Magnetic Resonance Imaging Brain Tumors

PubMed Central

Ciulla, Carlo; Veljanovski, Dimitar; Rechkoska Shikoska, Ustijana; Risteski, Filip A.

2015-01-01

This research presents signal-image post-processing techniques called Intensity-Curvature Measurement Approaches with application to the diagnosis of human brain tumors detected through Magnetic Resonance Imaging (MRI). Post-processing of the MRI of the human brain encompasses the following model functions: (i) bivariate cubic polynomial, (ii) bivariate cubic Lagrange polynomial, (iii) monovariate sinc, and (iv) bivariate linear. The following Intensity-Curvature Measurement Approaches were used: (i) classic-curvature, (ii) signal resilient to interpolation, (iii) intensity-curvature measure and (iv) intensity-curvature functional. The results revealed that the classic-curvature, the signal resilient to interpolation and the intensity-curvature functional are able to add additional information useful to the diagnosis carried out with MRI. The contribution to the MRI diagnosis of our study are: (i) the enhanced gray level scale of the tumor mass and the well-behaved representation of the tumor provided through the signal resilient to interpolation, and (ii) the visually perceptible third dimension perpendicular to the image plane provided through the classic-curvature and the intensity-curvature functional. PMID:26644943

On consciousness, resting state fMRI, and neurodynamics

PubMed Central

2010-01-01

Background During the last years, functional magnetic resonance imaging (fMRI) of the brain has been introduced as a new tool to measure consciousness, both in a clinical setting and in a basic neurocognitive research. Moreover, advanced mathematical methods and theories have arrived the field of fMRI (e.g. computational neuroimaging), and functional and structural brain connectivity can now be assessed non-invasively. Results The present work deals with a pluralistic approach to "consciousness'', where we connect theory and tools from three quite different disciplines: (1) philosophy of mind (emergentism and global workspace theory), (2) functional neuroimaging acquisitions, and (3) theory of deterministic and statistical neurodynamics – in particular the Wilson-Cowan model and stochastic resonance. Conclusions Based on recent experimental and theoretical work, we believe that the study of large-scale neuronal processes (activity fluctuations, state transitions) that goes on in the living human brain while examined with functional MRI during "resting state", can deepen our understanding of graded consciousness in a clinical setting, and clarify the concept of "consiousness" in neurocognitive and neurophilosophy research. PMID:20522270

The emerging potential of magnetic resonance imaging in personalizing radiotherapy for head and neck cancer: an oncologist's perspective.

PubMed

Wong, Kee H; Panek, Rafal; Bhide, Shreerang A; Nutting, Christopher M; Harrington, Kevin J; Newbold, Katie L

2017-03-01

Head and neck cancer (HNC) is a challenging tumour site for radiotherapy delivery owing to its complex anatomy and proximity to organs at risk (OARs) such as the spinal cord and optic apparatus. Despite significant advances in radiotherapy planning techniques, radiation-induced morbidities remain substantial. Further improvement would require high-quality imaging and tailored radiotherapy based on intratreatment response. For these reasons, the use of MRI in radiotherapy planning for HNC is rapidly gaining popularity. MRI provides superior soft-tissue contrast in comparison with CT, allowing better definition of the tumour and OARs. The lack of additional radiation exposure is another attractive feature for intratreatment monitoring. In addition, advanced MRI techniques such as diffusion-weighted, dynamic contrast-enhanced and intrinsic susceptibility-weighted MRI techniques are capable of characterizing tumour biology further by providing quantitative functional parameters such as tissue cellularity, vascular permeability/perfusion and hypoxia. These functional parameters are known to have radiobiological relevance, which potentially could guide treatment adaptation based on their changes prior to or during radiotherapy. In this article, we first present an overview of the applications of anatomical MRI sequences in head and neck radiotherapy, followed by the potentials and limitations of functional MRI sequences in personalizing therapy.

The emerging potential of magnetic resonance imaging in personalizing radiotherapy for head and neck cancer: an oncologist's perspective

PubMed Central

Panek, Rafal; Bhide, Shreerang A; Nutting, Christopher M; Harrington, Kevin J; Newbold, Katie L

2017-01-01

Head and neck cancer (HNC) is a challenging tumour site for radiotherapy delivery owing to its complex anatomy and proximity to organs at risk (OARs) such as the spinal cord and optic apparatus. Despite significant advances in radiotherapy planning techniques, radiation-induced morbidities remain substantial. Further improvement would require high-quality imaging and tailored radiotherapy based on intratreatment response. For these reasons, the use of MRI in radiotherapy planning for HNC is rapidly gaining popularity. MRI provides superior soft-tissue contrast in comparison with CT, allowing better definition of the tumour and OARs. The lack of additional radiation exposure is another attractive feature for intratreatment monitoring. In addition, advanced MRI techniques such as diffusion-weighted, dynamic contrast-enhanced and intrinsic susceptibility-weighted MRI techniques are capable of characterizing tumour biology further by providing quantitative functional parameters such as tissue cellularity, vascular permeability/perfusion and hypoxia. These functional parameters are known to have radiobiological relevance, which potentially could guide treatment adaptation based on their changes prior to or during radiotherapy. In this article, we first present an overview of the applications of anatomical MRI sequences in head and neck radiotherapy, followed by the potentials and limitations of functional MRI sequences in personalizing therapy. PMID:28256151

Self-Regulation of the Primary Auditory Cortex Attention Via Directed Attention Mediated By Real Time fMRI Neurofeedback

DTIC Science & Technology

2017-05-05

Directed Attention Mediated by Real -Time fMRI Neurofeedback presented at/published to 2017 Radiological Society of North America Conference in...DATE Sherwood - p.1 Self-regulation of the primary auditory cortex attention via directed attention mediated by real -time fMRI neurofeedback M S...auditory cortex hyperactivity by self-regulation of the primary auditory cortex (A 1) based on real -time functional magnetic resonance imaging neurofeedback

Objective assessment of olfactory function using functional magnetic resonance imaging.

PubMed

Toledano, Adolfo; Borromeo, Susana; Luna, Guillermo; Molina, Elena; Solana, Ana Beatriz; García-Polo, Pablo; Hernández, Juan Antonio; Álvarez-linera, Juan

2012-01-01

To show the results of a device that generates automated olfactory stimuli suitable for functional magnetic resonance imaging (fMRI) experiments. Ten normal volunteers, 5 women and 5 men, were studied. The system allows the programming of several sequences, providing the capability to synchronise the onset of odour presentation with acquisition by a trigger signal of the MRI scanner. The olfactometer is a device that allows selection of the odour, the event paradigm, the time of stimuli and the odour concentration. The paradigm used during fMRI scanning consisted of 15-s blocks. The odorant event took 2s with butanol, mint and coffee. We observed olfactory activity in the olfactory bulb, entorhinal cortex (4%), amygdala (2.5%) and temporo-parietal cortex, especially in the areas related to emotional integration. The device has demonstrated its effectiveness in stimulating olfactory areas and its capacity to adapt to fMRI equipment. Copyright © 2010 Elsevier España, S.L. All rights reserved.

WE-EF-BRD-01: Past, Present and Future: MRI-Guided Radiotherapy From 2005 to 2025

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

Lagendijk, J.

MRI-guided treatment is a growing area of medicine, particularly in radiotherapy and surgery. The exquisite soft tissue anatomic contrast offered by MRI, along with functional imaging, makes the use of MRI during therapeutic procedures very attractive. Challenging the utility of MRI in the therapy room are many issues including the physics of MRI and the impact on the environment and therapeutic instruments, the impact of the room and instruments on the MRI; safety, space, design and cost. In this session, the applications and challenges of MRI-guided treatment will be described. The session format is: Past, present and future: MRI-guided radiotherapymore » from 2005 to 2025: Jan Lagendijk Battling Maxwell’s equations: Physics challenges and solutions for hybrid MRI systems: Paul Keall I want it now!: Advances in MRI acquisition, reconstruction and the use of priors to enable fast anatomic and physiologic imaging to inform guidance and adaptation decisions: Yanle Hu MR in the OR: The growth and applications of MRI for interventional radiology and surgery: Rebecca Fahrig Learning Objectives: To understand the history and trajectory of MRI-guided radiotherapy To understand the challenges of integrating MR imaging systems with linear accelerators To understand the latest in fast MRI methods to enable the visualisation of anatomy and physiology on radiotherapy treatment timescales To understand the growing role and challenges of MRI for image-guided surgical procedures My disclosures are publicly available and updated at: http://sydney.edu.au/medicine/radiation-physics/about-us/disclosures.php.« less

Prediction of brain maturity in infants using machine-learning algorithms.

PubMed

Smyser, Christopher D; Dosenbach, Nico U F; Smyser, Tara A; Snyder, Abraham Z; Rogers, Cynthia E; Inder, Terrie E; Schlaggar, Bradley L; Neil, Jeffrey J

2016-08-01

Recent resting-state functional MRI investigations have demonstrated that much of the large-scale functional network architecture supporting motor, sensory and cognitive functions in older pediatric and adult populations is present in term- and prematurely-born infants. Application of new analytical approaches can help translate the improved understanding of early functional connectivity provided through these studies into predictive models of neurodevelopmental outcome. One approach to achieving this goal is multivariate pattern analysis, a machine-learning, pattern classification approach well-suited for high-dimensional neuroimaging data. It has previously been adapted to predict brain maturity in children and adolescents using structural and resting state-functional MRI data. In this study, we evaluated resting state-functional MRI data from 50 preterm-born infants (born at 23-29weeks of gestation and without moderate-severe brain injury) scanned at term equivalent postmenstrual age compared with data from 50 term-born control infants studied within the first week of life. Using 214 regions of interest, binary support vector machines distinguished term from preterm infants with 84% accuracy (p<0.0001). Inter- and intra-hemispheric connections throughout the brain were important for group categorization, indicating that widespread changes in the brain's functional network architecture associated with preterm birth are detectable by term equivalent age. Support vector regression enabled quantitative estimation of birth gestational age in single subjects using only term equivalent resting state-functional MRI data, indicating that the present approach is sensitive to the degree of disruption of brain development associated with preterm birth (using gestational age as a surrogate for the extent of disruption). This suggests that support vector regression may provide a means for predicting neurodevelopmental outcome in individual infants. Copyright © 2016 Elsevier Inc. All rights reserved.

Prediction of brain maturity in infants using machine-learning algorithms

PubMed Central

Smyser, Christopher D.; Dosenbach, Nico U.F.; Smyser, Tara A.; Snyder, Abraham Z.; Rogers, Cynthia E.; Inder, Terrie E.; Schlaggar, Bradley L.; Neil, Jeffrey J.

2016-01-01

Recent resting-state functional MRI investigations have demonstrated that much of the large-scale functional network architecture supporting motor, sensory and cognitive functions in older pediatric and adult populations is present in term- and prematurely-born infants. Application of new analytical approaches can help translate the improved understanding of early functional connectivity provided through these studies into predictive models of neurodevelopmental outcome. One approach to achieving this goal is multivariate pattern analysis, a machine-learning, pattern classification approach well-suited for high-dimensional neuroimaging data. It has previously been adapted to predict brain maturity in children and adolescents using structural and resting state-functional MRI data. In this study, we evaluated resting state-functional MRI data from 50 preterm-born infants (born at 23–29 weeks of gestation and without moderate–severe brain injury) scanned at term equivalent postmenstrual age compared with data from 50 term-born control infants studied within the first week of life. Using 214 regions of interest, binary support vector machines distinguished term from preterm infants with 84% accuracy (p < 0.0001). Inter- and intra-hemispheric connections throughout the brain were important for group categorization, indicating that widespread changes in the brain's functional network architecture associated with preterm birth are detectable by term equivalent age. Support vector regression enabled quantitative estimation of birth gestational age in single subjects using only term equivalent resting state-functional MRI data, indicating that the present approach is sensitive to the degree of disruption of brain development associated with preterm birth (using gestational age as a surrogate for the extent of disruption). This suggests that support vector regression may provide a means for predicting neurodevelopmental outcome in individual infants. PMID:27179605

Early myocardial dysfunction in streptozotocin-induced diabetic mice: a study using in vivo magnetic resonance imaging (MRI)

PubMed Central

Yu, Xichun; Tesiram, Yasvir A; Towner, Rheal A; Abbott, Andrew; Patterson, Eugene; Huang, Shijun; Garrett, Marion W; Chandrasekaran, Suresh; Matsuzaki, Satoshi; Szweda, Luke I; Gordon, Brian E; Kem, David C

2007-01-01

Background Diabetes is associated with a cardiomyopathy that is independent of coronary artery disease or hypertension. In the present study we used in vivo magnetic resonance imaging (MRI) and echocardiographic techniques to examine and characterize early changes in myocardial function in a mouse model of type 1 diabetes. Methods Diabetes was induced in 8-week old C57BL/6 mice with two intraperitoneal injections of streptozotocin. The blood glucose levels were maintained at 19–25 mmol/l using intermittent low dosages of long acting insulin glargine. MRI and echocardiography were performed at 4 weeks of diabetes (age of 12 weeks) in diabetic mice and age-matched controls. Results After 4 weeks of hyperglycemia one marker of mitochondrial function, NADH oxidase activity, was decreased to 50% of control animals. MRI studies of diabetic mice at 4 weeks demonstrated significant deficits in myocardial morphology and functionality including: a decreased left ventricular (LV) wall thickness, an increased LV end-systolic diameter and volume, a diminished LV ejection fraction and cardiac output, a decreased LV circumferential shortening, and decreased LV peak ejection and filling rates. M-mode echocardiographic and Doppler flow studies of diabetic mice at 4 weeks showed a decreased wall thickening and increased E/A ratio, supporting both systolic and diastolic dysfunction. Conclusion Our study demonstrates that MRI interrogation can identify the onset of diabetic cardiomyopathy in mice with its impaired functional capacity and altered morphology. The MRI technique will lend itself to repetitive study of early changes in cardiac function in small animal models of diabetic cardiomyopathy. PMID:17309798

Functional MRI evidence for fine motor praxis dysfunction in children with persistent speech disorders.

PubMed

Redle, Erin; Vannest, Jennifer; Maloney, Thomas; Tsevat, Rebecca K; Eikenberry, Sarah; Lewis, Barbara; Shriberg, Lawrence D; Tkach, Jean; Holland, Scott K

2015-02-09

Children with persistent speech disorders (PSD) often present with overt or subtle motor deficits; the possibility that speech disorders and motor deficits could arise from a shared neurological base is currently unknown. Functional MRI (fMRI) was used to examine the brain networks supporting fine motor praxis in children with PSD and without clinically identified fine motor deficits. This case-control study included 12 children with PSD (mean age 7.42 years, four female) and 12 controls (mean age 7.44 years, four female). Children completed behavioral evaluations using standardized motor assessments and parent reported functional measures. During fMRI scanning, participants completed a cued finger tapping task contrasted passive listening. A general linear model approach identified brain regions associated with finger tapping in each group and regions that differed between groups. The relationship between regional fMRI activation and fine motor skill was assessed using a regression analysis. Children with PSD had significantly poorer results for rapid speech production and fine motor praxis skills, but did not differ on classroom functional skills. Functional MRI results showed that children with PSD had significantly more activation in the cerebellum during finger tapping. Positive correlations between performance on a fine motor praxis test and activation multiple cortical regions were noted for children with PSD but not for controls. Over-activation in the cerebellum during a motor task may reflect a subtle abnormality in the non-speech motor neural circuitry in children with PSD. Copyright © 2014 Elsevier B.V. All rights reserved.

Identification and characterisation of midbrain nuclei using optimised functional magnetic resonance imaging

PubMed Central

Limbrick-Oldfield, Eve H.; Brooks, Jonathan C.W.; Wise, Richard J.S.; Padormo, Francesco; Hajnal, Jo V.; Beckmann, Christian F.; Ungless, Mark A.

2012-01-01

Localising activity in the human midbrain with conventional functional MRI (fMRI) is challenging because the midbrain nuclei are small and located in an area that is prone to physiological artefacts. Here we present a replicable and automated method to improve the detection and localisation of midbrain fMRI signals. We designed a visual fMRI task that was predicted would activate the superior colliculi (SC) bilaterally. A limited number of coronal slices were scanned, orientated along the long axis of the brainstem, whilst simultaneously recording cardiac and respiratory traces. A novel anatomical registration pathway was used to optimise the localisation of the small midbrain nuclei in stereotactic space. Two additional structural scans were used to improve registration between functional and structural T1-weighted images: an echo-planar image (EPI) that matched the functional data but had whole-brain coverage, and a whole-brain T2-weighted image. This pathway was compared to conventional registration pathways, and was shown to significantly improve midbrain registration. To reduce the physiological artefacts in the functional data, we estimated and removed structured noise using a modified version of a previously described physiological noise model (PNM). Whereas a conventional analysis revealed only unilateral SC activity, the PNM analysis revealed the predicted bilateral activity. We demonstrate that these methods improve the measurement of a biologically plausible fMRI signal. Moreover they could be used to investigate the function of other midbrain nuclei. PMID:21867762

[Does the individual adaptation of standardized speech paradigmas for clinical functional magnetic resonance imaging (fMRI) effect the localization of the language-dominant hemisphere and of Broca's and Wernicke's areas].

PubMed

Konrad, F; Nennig, E; Ochmann, H; Kress, B; Sartor, K; Stippich, C

2005-03-01

Functional magnetic resonance imaging (fMRI) localizes Broca's area (B) and Wernicke's area (W) and the hemisphere dominant for language. In clinical fMRI, adapting the stimulation paradigms to each patient's individual cognitive capacity is crucial for diagnostic success. To interpret clinical fMRI findings correctly, we studied the effect of varying frequency and number of stimuli on functional localization, determination of language dominance and BOLD signals. Ten volunteers (VP) were investigated at 1.5 Tesla during visually triggered sentence generation using a standardized block design. In four different measurements, the stimuli were presented to each VP with frequencies of 1/1 s, (1/2) s, (1/3) s and (1/6) s. The functional localizations and the correlations of the measured BOLD signals to the applied hemodynamic reference function (r) were almost independent from frequency and number of the stimuli in both hemispheres, whereas the relative BOLD signal changes (DeltaS) in B and W increased with the stimulation rate, which also changed the lateralization indices. The strongest BOLD activations were achieved with the highest stimulation rate or with the maximum language production task, respectively. The adaptation of language paradigms necessary in clinical fMRI does not alter the functional localizations but changes the BOLD signals and language lateralization which should not be attributed to the underlying brain pathology.

Fast periodic stimulation (FPS): a highly effective approach in fMRI brain mapping.

PubMed

Gao, Xiaoqing; Gentile, Francesco; Rossion, Bruno

2018-06-01

Defining the neural basis of perceptual categorization in a rapidly changing natural environment with low-temporal resolution methods such as functional magnetic resonance imaging (fMRI) is challenging. Here, we present a novel fast periodic stimulation (FPS)-fMRI approach to define face-selective brain regions with natural images. Human observers are presented with a dynamic stream of widely variable natural object images alternating at a fast rate (6 images/s). Every 9 s, a short burst of variable face images contrasting with object images in pairs induces an objective face-selective neural response at 0.111 Hz. A model-free Fourier analysis achieves a twofold increase in signal-to-noise ratio compared to a conventional block-design approach with identical stimuli and scanning duration, allowing to derive a comprehensive map of face-selective areas in the ventral occipito-temporal cortex, including the anterior temporal lobe (ATL), in all individual brains. Critically, periodicity of the desired category contrast and random variability among widely diverse images effectively eliminates the contribution of low-level visual cues, and lead to the highest values (80-90%) of test-retest reliability in the spatial activation map yet reported in imaging higher level visual functions. FPS-fMRI opens a new avenue for understanding brain function with low-temporal resolution methods.

High density event-related potential data acquisition in cognitive neuroscience.

PubMed

Slotnick, Scott D

2010-04-16

Functional magnetic resonance imaging (fMRI) is currently the standard method of evaluating brain function in the field of Cognitive Neuroscience, in part because fMRI data acquisition and analysis techniques are readily available. Because fMRI has excellent spatial resolution but poor temporal resolution, this method can only be used to identify the spatial location of brain activity associated with a given cognitive process (and reveals virtually nothing about the time course of brain activity). By contrast, event-related potential (ERP) recording, a method that is used much less frequently than fMRI, has excellent temporal resolution and thus can track rapid temporal modulations in neural activity. Unfortunately, ERPs are under utilized in Cognitive Neuroscience because data acquisition techniques are not readily available and low density ERP recording has poor spatial resolution. In an effort to foster the increased use of ERPs in Cognitive Neuroscience, the present article details key techniques involved in high density ERP data acquisition. Critically, high density ERPs offer the promise of excellent temporal resolution and good spatial resolution (or excellent spatial resolution if coupled with fMRI), which is necessary to capture the spatial-temporal dynamics of human brain function.

The power of using functional fMRI on small rodents to study brain pharmacology and disease

PubMed Central

Jonckers, Elisabeth; Shah, Disha; Hamaide, Julie; Verhoye, Marleen; Van der Linden, Annemie

2015-01-01

Functional magnetic resonance imaging (fMRI) is an excellent tool to study the effect of pharmacological modulations on brain function in a non-invasive and longitudinal manner. We introduce several blood oxygenation level dependent (BOLD) fMRI techniques, including resting state (rsfMRI), stimulus-evoked (st-fMRI), and pharmacological MRI (phMRI). Respectively, these techniques permit the assessment of functional connectivity during rest as well as brain activation triggered by sensory stimulation and/or a pharmacological challenge. The first part of this review describes the physiological basis of BOLD fMRI and the hemodynamic response on which the MRI contrast is based. Specific emphasis goes to possible effects of anesthesia and the animal’s physiological conditions on neural activity and the hemodynamic response. The second part of this review describes applications of the aforementioned techniques in pharmacologically induced, as well as in traumatic and transgenic disease models and illustrates how multiple fMRI methods can be applied successfully to evaluate different aspects of a specific disorder. For example, fMRI techniques can be used to pinpoint the neural substrate of a disease beyond previously defined hypothesis-driven regions-of-interest. In addition, fMRI techniques allow one to dissect how specific modifications (e.g., treatment, lesion etc.) modulate the functioning of specific brain areas (st-fMRI, phMRI) and how functional connectivity (rsfMRI) between several brain regions is affected, both in acute and extended time frames. Furthermore, fMRI techniques can be used to assess/explore the efficacy of novel treatments in depth, both in fundamental research as well as in preclinical settings. In conclusion, by describing several exemplary studies, we aim to highlight the advantages of functional MRI in exploring the acute and long-term effects of pharmacological substances and/or pathology on brain functioning along with several methodological considerations. PMID:26539115

Muscle MRI in patients with dysferlinopathy: pattern recognition and implications for clinical trials.

PubMed

Diaz-Manera, Jordi; Fernandez-Torron, Roberto; LLauger, Jaume; James, Meredith K; Mayhew, Anna; Smith, Fiona E; Moore, Ursula R; Blamire, Andrew M; Carlier, Pierre G; Rufibach, Laura; Mittal, Plavi; Eagle, Michelle; Jacobs, Marni; Hodgson, Tim; Wallace, Dorothy; Ward, Louise; Smith, Mark; Stramare, Roberto; Rampado, Alessandro; Sato, Noriko; Tamaru, Takeshi; Harwick, Bruce; Rico Gala, Susana; Turk, Suna; Coppenrath, Eva M; Foster, Glenn; Bendahan, David; Le Fur, Yann; Fricke, Stanley T; Otero, Hansel; Foster, Sheryl L; Peduto, Anthony; Sawyer, Anne Marie; Hilsden, Heather; Lochmuller, Hanns; Grieben, Ulrike; Spuler, Simone; Tesi Rocha, Carolina; Day, John W; Jones, Kristi J; Bharucha-Goebel, Diana X; Salort-Campana, Emmanuelle; Harms, Matthew; Pestronk, Alan; Krause, Sabine; Schreiber-Katz, Olivia; Walter, Maggie C; Paradas, Carmen; Hogrel, Jean-Yves; Stojkovic, Tanya; Takeda, Shin'ichi; Mori-Yoshimura, Madoka; Bravver, Elena; Sparks, Susan; Bello, Luca; Semplicini, Claudio; Pegoraro, Elena; Mendell, Jerry R; Bushby, Kate; Straub, Volker

2018-05-07

Dysferlinopathies are a group of muscle disorders caused by mutations in the DYSF gene. Previous muscle imaging studies describe a selective pattern of muscle involvement in smaller patient cohorts, but a large imaging study across the entire spectrum of the dysferlinopathies had not been performed and previous imaging findings were not correlated with functional tests. We present cross-sectional T1-weighted muscle MRI data from 182 patients with genetically confirmed dysferlinopathies. We have analysed the pattern of muscles involved in the disease using hierarchical analysis and presented it as heatmaps. Results of the MRI scans have been correlated with relevant functional tests for each region of the body analysed. In 181 of the 182 patients scanned, we observed muscle pathology on T1-weighted images, with the gastrocnemius medialis and the soleus being the most commonly affected muscles. A similar pattern of involvement was identified in most patients regardless of their clinical presentation. Increased muscle pathology on MRI correlated positively with disease duration and functional impairment. The information generated by this study is of high diagnostic value and important for clinical trial development. We have been able to describe a pattern that can be considered as characteristic of dysferlinopathy. We have defined the natural history of the disease from a radiological point of view. These results enabled the identification of the most relevant regions of interest for quantitative MRI in longitudinal studies, such as clinical trials. NCT01676077. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Comparative sensitivities of functional MRI sequences in detection of local recurrence of prostate carcinoma after radical prostatectomy or external-beam radiotherapy.

PubMed

Roy, Catherine; Foudi, Fatah; Charton, Jeanne; Jung, Michel; Lang, Hervé; Saussine, Christian; Jacqmin, Didier

2013-04-01

The aim of this retrospective study was to determine the respective accuracies of three types of functional MRI sequences-diffusion-weighted imaging (DWI), dynamic contrast-enhanced (DCE) MRI, and 3D (1)H-MR spectroscopy (MRS)-in the depiction of local prostate cancer recurrence after two different initial therapy options. From a cohort of 83 patients with suspicion of local recurrence based on prostate-specific antigen (PSA) kinetics who were imaged on a 3-T MRI unit using an identical protocol including the three functional sequences with an endorectal coil, we selected 60 patients (group A, 28 patients who underwent radical prostatectomy; group B, 32 patients who underwent external-beam radiation) who had local recurrence ascertained on the basis of a transrectal ultrasound-guided biopsy results and a reduction in PSA level after salvage therapy. All patients presented with a local relapse. Sensitivity with T2-weighted MRI and 3D (1)H-MRS sequences was 57% and 53%, respectively, for group A and 71% and 78%, respectively, for group B. DCE-MRI alone showed a sensitivity of 100% and 96%, respectively, for groups A and B. DWI alone had a higher sensitivity for group B (96%) than for group A (71%). The combination of T2-weighted imaging plus DWI plus DCE-MRI provided a sensitivity as high as 100% in group B. The performance of functional imaging sequences for detecting recurrence is different after radical prostatectomy and external-beam radiotherapy. DCE-MRI is a valid and efficient tool to detect prostate cancer recurrence in radical prostatectomy as well as in external-beam radiotherapy. The combination of DCE-MRI and DWI is highly efficient after radiation therapy. Three-dimensional (1)H-MRS needs to be improved. Even though it is not accurate enough, T2-weighted imaging remains essential for the morphologic analysis of the area.

Integrating EEG and fMRI in epilepsy.

PubMed

Formaggio, Emanuela; Storti, Silvia Francesca; Bertoldo, Alessandra; Manganotti, Paolo; Fiaschi, Antonio; Toffolo, Gianna Maria

2011-02-14

Integrating electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) studies enables to non-invasively investigate human brain function and to find the direct correlation of these two important measures of brain activity. Presurgical evaluation of patients with epilepsy is one of the areas where EEG and fMRI integration has considerable clinical relevance for localizing the brain regions generating interictal epileptiform activity. The conventional analysis of EEG-fMRI data is based on the visual identification of the interictal epileptiform discharges (IEDs) on scalp EEG. The convolution of these EEG events, represented as stick functions, with a model of the fMRI response, i.e. the hemodynamic response function, provides the regressor for general linear model (GLM) analysis of fMRI data. However, the conventional analysis is not automatic and suffers of some subjectivity in IEDs classification. Here, we present an easy-to-use and automatic approach for combined EEG-fMRI analysis able to improve IEDs identification based on Independent Component Analysis and wavelet analysis. EEG signal due to IED is reconstructed and its wavelet power is used as a regressor in GLM. The method was validated on simulated data and then applied on real data set consisting of 2 normal subjects and 5 patients with partial epilepsy. In all continuous EEG-fMRI recording sessions a good quality EEG was obtained allowing the detection of spontaneous IEDs and the analysis of the related BOLD activation. The main clinical finding in EEG-fMRI studies of patients with partial epilepsy is that focal interictal slow-wave activity was invariably associated with increased focal BOLD responses in a spatially related brain area. Our study extends current knowledge on epileptic foci localization and confirms previous reports suggesting that BOLD activation associated with slow activity might have a role in localizing the epileptogenic region even in the absence of clear interictal spikes. Copyright © 2010 Elsevier Inc. All rights reserved.

fMRI Validation of fNIRS Measurements During a Naturalistic Task

PubMed Central

Noah, J. Adam; Ono, Yumie; Nomoto, Yasunori; Shimada, Sotaro; Tachibana, Atsumichi; Zhang, Xian; Bronner, Shaw; Hirsch, Joy

2015-01-01

We present a method to compare brain activity recorded with near-infrared spectroscopy (fNIRS) in a dance video game task to that recorded in a reduced version of the task using fMRI (functional magnetic resonance imaging). Recently, it has been shown that fNIRS can accurately record functional brain activities equivalent to those concurrently recorded with functional magnetic resonance imaging for classic psychophysical tasks and simple finger tapping paradigms. However, an often quoted benefit of fNIRS is that the technique allows for studying neural mechanisms of complex, naturalistic behaviors that are not possible using the constrained environment of fMRI. Our goal was to extend the findings of previous studies that have shown high correlation between concurrently recorded fNIRS and fMRI signals to compare neural recordings obtained in fMRI procedures to those separately obtained in naturalistic fNIRS experiments. Specifically, we developed a modified version of the dance video game Dance Dance Revolution (DDR) to be compatible with both fMRI and fNIRS imaging procedures. In this methodology we explain the modifications to the software and hardware for compatibility with each technique as well as the scanning and calibration procedures used to obtain representative results. The results of the study show a task-related increase in oxyhemoglobin in both modalities and demonstrate that it is possible to replicate the findings of fMRI using fNIRS in a naturalistic task. This technique represents a methodology to compare fMRI imaging paradigms which utilize a reduced-world environment to fNIRS in closer approximation to naturalistic, full-body activities and behaviors. Further development of this technique may apply to neurodegenerative diseases, such as Parkinson’s disease, late states of dementia, or those with magnetic susceptibility which are contraindicated for fMRI scanning. PMID:26132365

An in vivo MRI Template Set for Morphometry, Tissue Segmentation, and fMRI Localization in Rats

PubMed Central

Valdés-Hernández, Pedro Antonio; Sumiyoshi, Akira; Nonaka, Hiroi; Haga, Risa; Aubert-Vásquez, Eduardo; Ogawa, Takeshi; Iturria-Medina, Yasser; Riera, Jorge J.; Kawashima, Ryuta

2011-01-01

Over the last decade, several papers have focused on the construction of highly detailed mouse high field magnetic resonance image (MRI) templates via non-linear registration to unbiased reference spaces, allowing for a variety of neuroimaging applications such as robust morphometric analyses. However, work in rats has only provided medium field MRI averages based on linear registration to biased spaces with the sole purpose of approximate functional MRI (fMRI) localization. This precludes any morphometric analysis in spite of the need of exploring in detail the neuroanatomical substrates of diseases in a recent advent of rat models. In this paper we present a new in vivo rat T2 MRI template set, comprising average images of both intensity and shape, obtained via non-linear registration. Also, unlike previous rat template sets, we include white and gray matter probabilistic segmentations, expanding its use to those applications demanding prior-based tissue segmentation, e.g., statistical parametric mapping (SPM) voxel-based morphometry. We also provide a preliminary digitalization of latest Paxinos and Watson atlas for anatomical and functional interpretations within the cerebral cortex. We confirmed that, like with previous templates, forepaw and hindpaw fMRI activations can be correctly localized in the expected atlas structure. To exemplify the use of our new MRI template set, were reported the volumes of brain tissues and cortical structures and probed their relationships with ontogenetic development. Other in vivo applications in the near future can be tensor-, deformation-, or voxel-based morphometry, morphological connectivity, and diffusion tensor-based anatomical connectivity. Our template set, freely available through the SPM extension website, could be an important tool for future longitudinal and/or functional extensive preclinical studies. PMID:22275894

A Graphics Processing Unit Accelerated Motion Correction Algorithm and Modular System for Real-time fMRI

PubMed Central

Scheinost, Dustin; Hampson, Michelle; Qiu, Maolin; Bhawnani, Jitendra; Constable, R. Todd; Papademetris, Xenophon

2013-01-01

Real-time functional magnetic resonance imaging (rt-fMRI) has recently gained interest as a possible means to facilitate the learning of certain behaviors. However, rt-fMRI is limited by processing speed and available software, and continued development is needed for rt-fMRI to progress further and become feasible for clinical use. In this work, we present an open-source rt-fMRI system for biofeedback powered by a novel Graphics Processing Unit (GPU) accelerated motion correction strategy as part of the BioImage Suite project (www.bioimagesuite.org). Our system contributes to the development of rt-fMRI by presenting a motion correction algorithm that provides an estimate of motion with essentially no processing delay as well as a modular rt-fMRI system design. Using empirical data from rt-fMRI scans, we assessed the quality of motion correction in this new system. The present algorithm performed comparably to standard (non real-time) offline methods and outperformed other real-time methods based on zero order interpolation of motion parameters. The modular approach to the rt-fMRI system allows the system to be flexible to the experiment and feedback design, a valuable feature for many applications. We illustrate the flexibility of the system by describing several of our ongoing studies. Our hope is that continuing development of open-source rt-fMRI algorithms and software will make this new technology more accessible and adaptable, and will thereby accelerate its application in the clinical and cognitive neurosciences. PMID:23319241

A graphics processing unit accelerated motion correction algorithm and modular system for real-time fMRI.

PubMed

Scheinost, Dustin; Hampson, Michelle; Qiu, Maolin; Bhawnani, Jitendra; Constable, R Todd; Papademetris, Xenophon

2013-07-01

Real-time functional magnetic resonance imaging (rt-fMRI) has recently gained interest as a possible means to facilitate the learning of certain behaviors. However, rt-fMRI is limited by processing speed and available software, and continued development is needed for rt-fMRI to progress further and become feasible for clinical use. In this work, we present an open-source rt-fMRI system for biofeedback powered by a novel Graphics Processing Unit (GPU) accelerated motion correction strategy as part of the BioImage Suite project ( www.bioimagesuite.org ). Our system contributes to the development of rt-fMRI by presenting a motion correction algorithm that provides an estimate of motion with essentially no processing delay as well as a modular rt-fMRI system design. Using empirical data from rt-fMRI scans, we assessed the quality of motion correction in this new system. The present algorithm performed comparably to standard (non real-time) offline methods and outperformed other real-time methods based on zero order interpolation of motion parameters. The modular approach to the rt-fMRI system allows the system to be flexible to the experiment and feedback design, a valuable feature for many applications. We illustrate the flexibility of the system by describing several of our ongoing studies. Our hope is that continuing development of open-source rt-fMRI algorithms and software will make this new technology more accessible and adaptable, and will thereby accelerate its application in the clinical and cognitive neurosciences.

MRI with and without a high-density EEG cap--what makes the difference?

PubMed

Klein, Carina; Hänggi, Jürgen; Luechinger, Roger; Jäncke, Lutz

2015-02-01

Besides the benefit of combining electroencephalography (EEG) and magnetic resonance imaging (MRI), much effort has been spent to develop algorithms aimed at successfully cleaning the EEG data from MRI-related gradient and ballistocardiological artifacts. However, there are also studies showing a negative influence of the EEG on MRI data quality. Therefore, in the present study, we focused for the first time on the influence of the EEG on morphometric measurements of T1-weighted MRI data (voxel- and surfaced-based morphometry). Here, we demonstrate a strong influence of the EEG on cortical thickness, surface area, and volume as well as subcortical volumes due to local EEG-related inhomogeneities of the static magnetic (B0) and the gradient field (B1). In a second step, we analyzed the signal-to-noise ratios for both the anatomical and the functional data when recorded simultaneously with EEG and MRI and compared them to the ratios of the MRI data without simultaneous EEG measurements. These analyses revealed consistently lower signal-to-noise ratios for anatomical as well as functional MRI data during simultaneous EEG registration. In contrast, further analyses of T2*-weighted images provided reliable results independent of whether including the individuals' T1-weighted image with or without the EEG cap in the fMRI preprocessing stream. Based on our findings, we strongly recommend against using the structural images obtained during simultaneous EEG-MRI recordings for further anatomical data analysis. Copyright © 2014 Elsevier Inc. All rights reserved.

Imaging drugs with and without clinical analgesic efficacy.

PubMed

Upadhyay, Jaymin; Anderson, Julie; Schwarz, Adam J; Coimbra, Alexandre; Baumgartner, Richard; Pendse, G; George, Edward; Nutile, Lauren; Wallin, Diana; Bishop, James; Neni, Saujanya; Maier, Gary; Iyengar, Smriti; Evelhoch, Jeffery L; Bleakman, David; Hargreaves, Richard; Becerra, Lino; Borsook, David

2011-12-01

The behavioral response to pain is driven by sensory and affective components, each of which is mediated by the CNS. Subjective pain ratings are used as readouts when appraising potential analgesics; however, pain ratings alone cannot enable a characterization of CNS pain circuitry during pain processing or how this circuitry is modulated pharmacologically. Having a more objective readout of potential analgesic effects may allow improved understanding and detection of pharmacological efficacy for pain. The pharmacological/functional magnetic resonance imaging (phMRI/fMRI) methodology can be used to objectively evaluate drug action on the CNS. In this context, we aimed to evaluate two drugs that had been developed as analgesics: one that is efficacious for pain (buprenorphine (BUP)) and one that failed as an analgesic in clinical trials aprepitant (APREP). Using phMRI, we observed that activation induced solely by BUP was present in regions with μ-opioid receptors, whereas APREP-induced activation was seen in regions expressing NK(1) receptors. However, significant pharmacological modulation of functional connectivity in pain-processing pathways was only observed following BUP administration. By implementing an evoked pain fMRI paradigm, these drugs could also be differentiated by comparing the respective fMRI signals in CNS circuits mediating sensory and affective components of pain. We report a correlation of functional connectivity and evoked pain fMRI measures with pain ratings as well as peak drug concentration. This investigation demonstrates how CNS-acting drugs can be compared, and how the phMRI/fMRI methodology may be used with conventional measures to better evaluate candidate analgesics in small subject cohorts.

Imaging Drugs with and without Clinical Analgesic Efficacy

PubMed Central

Upadhyay, Jaymin; Anderson, Julie; Schwarz, Adam J; Coimbra, Alexandre; Baumgartner, Richard; Pendse, G; George, Edward; Nutile, Lauren; Wallin, Diana; Bishop, James; Neni, Saujanya; Maier, Gary; Iyengar, Smriti; Evelhoch, Jeffery L; Bleakman, David; Hargreaves, Richard; Becerra, Lino; Borsook, David

2011-01-01

The behavioral response to pain is driven by sensory and affective components, each of which is mediated by the CNS. Subjective pain ratings are used as readouts when appraising potential analgesics; however, pain ratings alone cannot enable a characterization of CNS pain circuitry during pain processing or how this circuitry is modulated pharmacologically. Having a more objective readout of potential analgesic effects may allow improved understanding and detection of pharmacological efficacy for pain. The pharmacological/functional magnetic resonance imaging (phMRI/fMRI) methodology can be used to objectively evaluate drug action on the CNS. In this context, we aimed to evaluate two drugs that had been developed as analgesics: one that is efficacious for pain (buprenorphine (BUP)) and one that failed as an analgesic in clinical trials aprepitant (APREP). Using phMRI, we observed that activation induced solely by BUP was present in regions with μ-opioid receptors, whereas APREP-induced activation was seen in regions expressing NK1 receptors. However, significant pharmacological modulation of functional connectivity in pain-processing pathways was only observed following BUP administration. By implementing an evoked pain fMRI paradigm, these drugs could also be differentiated by comparing the respective fMRI signals in CNS circuits mediating sensory and affective components of pain. We report a correlation of functional connectivity and evoked pain fMRI measures with pain ratings as well as peak drug concentration. This investigation demonstrates how CNS-acting drugs can be compared, and how the phMRI/fMRI methodology may be used with conventional measures to better evaluate candidate analgesics in small subject cohorts. PMID:21849979

In vivo functional connectome of human brainstem nuclei of the ascending arousal, autonomic, and motor systems by high spatial resolution 7-Tesla fMRI.

PubMed

Bianciardi, Marta; Toschi, Nicola; Eichner, Cornelius; Polimeni, Jonathan R; Setsompop, Kawin; Brown, Emery N; Hämäläinen, Matti S; Rosen, Bruce R; Wald, Lawrence L

2016-06-01

Our aim was to map the in vivo human functional connectivity of several brainstem nuclei with the rest of the brain by using seed-based correlation of ultra-high magnetic field functional magnetic resonance imaging (fMRI) data. We used the recently developed template of 11 brainstem nuclei derived from multi-contrast structural MRI at 7 Tesla as seed regions to determine their connectivity to the rest of the brain. To achieve this, we used the increased contrast-to-noise ratio of 7-Tesla fMRI compared with 3 Tesla and time-efficient simultaneous multi-slice imaging to cover the brain with high spatial resolution (1.1-mm isotropic nominal resolution) while maintaining a short repetition time (2.5 s). The delineated Pearson's correlation-based functional connectivity diagrams (connectomes) of 11 brainstem nuclei of the ascending arousal, motor, and autonomic systems from 12 controls are presented and discussed in the context of existing histology and animal work. Considering that the investigated brainstem nuclei play a crucial role in several vital functions, the delineated preliminary connectomes might prove useful for future in vivo research and clinical studies of human brainstem function and pathology, including disorders of consciousness, sleep disorders, autonomic disorders, Parkinson's disease, and other motor disorders.

Added Value of Assessing Adnexal Masses with Advanced MRI Techniques

PubMed Central

Thomassin-Naggara, I.; Balvay, D.; Rockall, A.; Carette, M. F.; Ballester, M.; Darai, E.; Bazot, M.

2015-01-01

This review will present the added value of perfusion and diffusion MR sequences to characterize adnexal masses. These two functional MR techniques are readily available in routine clinical practice. We will describe the acquisition parameters and a method of analysis to optimize their added value compared with conventional images. We will then propose a model of interpretation that combines the anatomical and morphological information from conventional MRI sequences with the functional information provided by perfusion and diffusion weighted sequences. PMID:26413542

Alzheimer disease brain atrophy subtypes are associated with cognition and rate of decline.

PubMed

Risacher, Shannon L; Anderson, Wesley H; Charil, Arnaud; Castelluccio, Peter F; Shcherbinin, Sergey; Saykin, Andrew J; Schwarz, Adam J

2017-11-21

To test the hypothesis that cortical and hippocampal volumes, measured in vivo from volumetric MRI (vMRI) scans, could be used to identify variant subtypes of Alzheimer disease (AD) and to prospectively predict the rate of clinical decline. Amyloid-positive participants with AD from the Alzheimer's Disease Neuroimaging Initiative (ADNI) 1 and ADNI2 with baseline MRI scans (n = 229) and 2-year clinical follow-up (n = 100) were included. AD subtypes (hippocampal sparing [HpSp MRI ], limbic predominant [LP MRI ], typical AD [tAD MRI ]) were defined according to an algorithm analogous to one recently proposed for tau neuropathology. Relationships between baseline hippocampal volume to cortical volume ratio (HV:CTV) and clinical variables were examined by both continuous regression and categorical models. When participants were divided categorically, the HpSp MRI group showed significantly more AD-like hypometabolism on 18 F-fluorodeoxyglucose-PET ( p < 0.05) and poorer baseline executive function ( p < 0.001). Other baseline clinical measures did not differ across the 3 groups. Participants with HpSp MRI also showed faster subsequent clinical decline than participants with LP MRI on the Alzheimer's Disease Assessment Scale, 13-Item Subscale (ADAS-Cog 13 ), Mini-Mental State Examination (MMSE), and Functional Assessment Questionnaire (all p < 0.05) and tAD MRI on the MMSE and Clinical Dementia Rating Sum of Boxes (CDR-SB) (both p < 0.05). Finally, a larger HV:CTV was associated with poorer baseline executive function and a faster slope of decline in CDR-SB, MMSE, and ADAS-Cog 13 score ( p < 0.05). These associations were driven mostly by the amount of cortical rather than hippocampal atrophy. AD subtypes with phenotypes consistent with those observed with tau neuropathology can be identified in vivo with vMRI. An increased HV:CTV ratio was predictive of faster clinical decline in participants with AD who were clinically indistinguishable at baseline except for a greater dysexecutive presentation. © 2017 American Academy of Neurology.

Comparison of brain MRI findings with language and motor function in the dystroglycanopathies.

PubMed

Brun, Brianna N; Mockler, Shelley R H; Laubscher, Katie M; Stephan, Carrie M; Wallace, Anne M; Collison, Julia A; Zimmerman, M Bridget; Dobyns, William B; Mathews, Katherine D

2017-02-14

To describe the spectrum of brain MRI findings in a cohort of individuals with dystroglycanopathies (DGs) and relate MRI results to function. All available brain MRIs done for clinical indications on individuals enrolled in a DG natural history study (NCT00313677) were reviewed. Reports were reviewed when MRI was not available. MRIs were categorized as follows: (1) cortical, brainstem, and cerebellar malformations; (2) cortical and cerebellar malformations; or (3) normal. Language development was assigned to 1 of 3 categories by a speech pathologist. Maximal motor function and presence of epilepsy were determined by history or examination. Twenty-five MRIs and 9 reports were reviewed. The most common MRI abnormalities were cobblestone cortex or dysgyria with an anterior-posterior gradient and cerebellar hypoplasia. Seven individuals had MRIs in group 1, 8 in group 2, and 19 in group 3. Language was impaired in 100% of those in MRI groups 1 and 2, and degree of language impairment correlated with severity of imaging. Eighty-five percent of the whole group achieved independent walking, but only 33% did in group 1. Epilepsy was present in 8% of the cohort and rose to 37% of those with an abnormal MRI. Developmental abnormalities of the brain such as cobblestone lissencephaly, cerebellar cysts, pontine hypoplasia, and brainstem bowing are hallmarks of DG and should prompt consideration of these diagnoses. Brain imaging in individuals with DG helps to predict outcomes, especially language development, aiding clinicians in prognostic counseling. © 2017 American Academy of Neurology.

Three-way ROC validation of rs-fMRI visual information propagation transfer functions used to differentiate between RRMS and CIS optic neuritis patients.

PubMed

Farahani, Ehsan Shahrabi; Choudhury, Samiul H; Cortese, Filomeno; Costello, Fiona; Goodyear, Bradley; Smith, Michael R

2017-07-01

Resting-state fMRI (rs-fMRI) measures the temporal synchrony between different brain regions while the subject is at rest. We present an investigation using visual information propagation transfer functions as potential optic neuritis (ON) markers for the pathways between the lateral geniculate nuclei, the primary visual cortex, the lateral occipital cortex and the superior parietal cortex. We investigate marker reliability in differentiating between healthy controls and ON patients with clinically isolated syndrome (CIS), and relapsing-remitting multiple sclerosis (RRMS) using a three-way receiver operating characteristics analysis. We identify useful and reliable three-way ON related metrics in the rs-fMRI low-frequency band 0.0 Hz to 0.1 Hz, with potential markers associated with the higher frequency harmonics of these signals in the 0.1 Hz to 0.2 Hz and 0.2 Hz to 0.3 Hz bands.

Resting-State Functional Connectivity in Autism Spectrum Disorders: A Review

PubMed Central

Hull, Jocelyn V.; Jacokes, Zachary J.; Torgerson, Carinna M.; Irimia, Andrei; Van Horn, John Darrell

2017-01-01

Ongoing debate exists within the resting-state functional MRI (fMRI) literature over how intrinsic connectivity is altered in the autistic brain, with reports of general over-connectivity, under-connectivity, and/or a combination of both. Classifying autism using brain connectivity is complicated by the heterogeneous nature of the condition, allowing for the possibility of widely variable connectivity patterns among individuals with the disorder. Further differences in reported results may be attributable to the age and sex of participants included, designs of the resting-state scan, and to the analysis technique used to evaluate the data. This review systematically examines the resting-state fMRI autism literature to date and compares studies in an attempt to draw overall conclusions that are presently challenging. We also propose future direction for rs-fMRI use to categorize individuals with autism spectrum disorder, serve as a possible diagnostic tool, and best utilize data-sharing initiatives. PMID:28101064

The potential of multiparametric MRI of the breast

PubMed Central

Pinker, Katja; Helbich, Thomas H

2017-01-01

MRI is an essential tool in breast imaging, with multiple established indications. Dynamic contrast-enhanced MRI (DCE-MRI) is the backbone of any breast MRI protocol and has an excellent sensitivity and good specificity for breast cancer diagnosis. DCE-MRI provides high-resolution morphological information, as well as some functional information about neoangiogenesis as a tumour-specific feature. To overcome limitations in specificity, several other functional MRI parameters have been investigated and the application of these combined parameters is defined as multiparametric MRI (mpMRI) of the breast. MpMRI of the breast can be performed at different field strengths (1.5–7 T) and includes both established (diffusion-weighted imaging, MR spectroscopic imaging) and novel MRI parameters (sodium imaging, chemical exchange saturation transfer imaging, blood oxygen level-dependent MRI), as well as hybrid imaging with positron emission tomography (PET)/MRI and different radiotracers. Available data suggest that multiparametric imaging using different functional MRI and PET parameters can provide detailed information about the underlying oncogenic processes of cancer development and progression and can provide additional specificity. This article will review the current and emerging functional parameters for mpMRI of the breast for improved diagnostic accuracy in breast cancer. PMID:27805423

Differences in Processing of Taxonomic and Sequential Relations in Semantic Memory: An fMRI Investigation

ERIC Educational Resources Information Center

Kuchinke, Lars; van der Meer, Elke; Krueger, Frank

2009-01-01

Conceptual knowledge of our world is represented in semantic memory in terms of concepts and semantic relations between concepts. We used functional magnetic resonance imaging (fMRI) to examine the cortical regions underlying the processing of sequential and taxonomic relations. Participants were presented verbal cues and performed three tasks:…

Perceiving Age and Gender in Unfamiliar Faces: An fMRI Study on Face Categorization

ERIC Educational Resources Information Center

Wiese, Holger; Kloth, Nadine; Gullmar, Daniel; Reichenbach, Jurgen R.; Schweinberger, Stefan R.

2012-01-01

Efficient processing of unfamiliar faces typically involves their categorization (e.g., into old vs. young or male vs. female). However, age and gender categorization may pose different perceptual demands. In the present study, we employed functional magnetic resonance imaging (fMRI) to compare the activity evoked during age vs. gender…

Measuring speaker–listener neural coupling with functional near infrared spectroscopy

PubMed Central

Liu, Yichuan; Piazza, Elise A.; Simony, Erez; Shewokis, Patricia A.; Onaral, Banu; Hasson, Uri; Ayaz, Hasan

2017-01-01

The present study investigates brain-to-brain coupling, defined as inter-subject correlations in the hemodynamic response, during natural verbal communication. We used functional near-infrared spectroscopy (fNIRS) to record brain activity of 3 speakers telling stories and 15 listeners comprehending audio recordings of these stories. Listeners’ brain activity was significantly correlated with speakers’ with a delay. This between-brain correlation disappeared when verbal communication failed. We further compared the fNIRS and functional Magnetic Resonance Imaging (fMRI) recordings of listeners comprehending the same story and found a significant relationship between the fNIRS oxygenated-hemoglobin concentration changes and the fMRI BOLD in brain areas associated with speech comprehension. This correlation between fNIRS and fMRI was only present when data from the same story were compared between the two modalities and vanished when data from different stories were compared; this cross-modality consistency further highlights the reliability of the spatiotemporal brain activation pattern as a measure of story comprehension. Our findings suggest that fNIRS can be used for investigating brain-to-brain coupling during verbal communication in natural settings. PMID:28240295

Error-related processing following severe traumatic brain injury: An event-related functional magnetic resonance imaging (fMRI) study

PubMed Central

Sozda, Christopher N.; Larson, Michael J.; Kaufman, David A.S.; Schmalfuss, Ilona M.; Perlstein, William M.

2011-01-01

Continuous monitoring of one’s performance is invaluable for guiding behavior towards successful goal attainment by identifying deficits and strategically adjusting responses when performance is inadequate. In the present study, we exploited the advantages of event-related functional magnetic resonance imaging (fMRI) to examine brain activity associated with error-related processing after severe traumatic brain injury (sTBI). fMRI and behavioral data were acquired while 10 sTBI participants and 12 neurologically-healthy controls performed a task-switching cued-Stroop task. fMRI data were analyzed using a random-effects whole-brain voxel-wise general linear model and planned linear contrasts. Behaviorally, sTBI patients showed greater error-rate interference than neurologically-normal controls. fMRI data revealed that, compared to controls, sTBI patients showed greater magnitude error-related activation in the anterior cingulate cortex (ACC) and an increase in the overall spatial extent of error-related activation across cortical and subcortical regions. Implications for future research and potential limitations in conducting fMRI research in neurologically-impaired populations are discussed, as well as some potential benefits of employing multimodal imaging (e.g., fMRI and event-related potentials) of cognitive control processes in TBI. PMID:21756946

Error-related processing following severe traumatic brain injury: an event-related functional magnetic resonance imaging (fMRI) study.

PubMed

Sozda, Christopher N; Larson, Michael J; Kaufman, David A S; Schmalfuss, Ilona M; Perlstein, William M

2011-10-01

Continuous monitoring of one's performance is invaluable for guiding behavior towards successful goal attainment by identifying deficits and strategically adjusting responses when performance is inadequate. In the present study, we exploited the advantages of event-related functional magnetic resonance imaging (fMRI) to examine brain activity associated with error-related processing after severe traumatic brain injury (sTBI). fMRI and behavioral data were acquired while 10 sTBI participants and 12 neurologically-healthy controls performed a task-switching cued-Stroop task. fMRI data were analyzed using a random-effects whole-brain voxel-wise general linear model and planned linear contrasts. Behaviorally, sTBI patients showed greater error-rate interference than neurologically-normal controls. fMRI data revealed that, compared to controls, sTBI patients showed greater magnitude error-related activation in the anterior cingulate cortex (ACC) and an increase in the overall spatial extent of error-related activation across cortical and subcortical regions. Implications for future research and potential limitations in conducting fMRI research in neurologically-impaired populations are discussed, as well as some potential benefits of employing multimodal imaging (e.g., fMRI and event-related potentials) of cognitive control processes in TBI. Copyright © 2011 Elsevier B.V. All rights reserved.

Comprehensive Review on Magnetic Resonance Imaging in Alzheimer's Disease.

PubMed

Dona, Olga; Thompson, Jeff; Druchok, Cheryl

2016-01-01

Alzheimer's disease (AD) is the most common cause of dementia in the elderly. However, definitive diagnosis of AD is only achievable postmortem and currently relies on clinical neurological evaluation. Magnetic resonance imaging (MRI) can evaluate brain changes typical of AD, including brain atrophy, presence of amyloid β (Aβ) plaques, and functional and biochemical abnormalities. Structural MRI (sMRI) has historically been used to assess the inherent brain atrophy present in AD. However, new techniques have recently emerged that have refined sMRI into a more precise tool to quantify the thickness and volume of AD-sensitive cerebral structures. Aβ plaques, a defining pathology of AD, are widely believed to contribute to the progressive cognitive decline in AD, but accurate assessment is only possible on autopsy. In vivo MRI of plaques, although currently limited to mouse models of AD, is a very promising technique. Measuring changes in activation and connectivity in AD-specific regions of the brain can be performed with functional MRI (fMRI). To help distinguish AD from diseases with similar symptoms, magnetic resonance spectroscopy (MRS) can be used to look for differing metabolite concentrations in vivo. Together, these MR techniques, evaluating various brain changes typical of AD, may help to provide a more definitive diagnosis and ease the assessment of the disease over time, noninvasively.

[Research progress of functional magnetic resonance imaging in mechanism studies of tinnitus].

PubMed

Ji, B B; Li, M; Zhang, J N

2018-02-07

Tinnitus is a subjective symptom of phantom sound in the ear or brain without sound or electrical stimulation in the environment. The mechanism of tinnitus is complicated and mostly unclear. Recent studies suggested that the abnormal peripheral auditory input lead to neuroplasticity changes in central nervous system followed by tinnitus. More research concerned on the tinnitus central mechanism. A rapid development of functional magnetic resonance imaging (fMRI) technique made it more widely used in tinnitus central mechanism research. fMRI brought new findings but also presented some shortages in technology and cognition in tinnitus study. This article summarized the outcomes of fMRI research on tinnitus in recent years, exploring its existing problems and application prospects.

Quantitative prediction of perceptual decisions during near-threshold fear detection

NASA Astrophysics Data System (ADS)

Pessoa, Luiz; Padmala, Srikanth

2005-04-01

A fundamental goal of cognitive neuroscience is to explain how mental decisions originate from basic neural mechanisms. The goal of the present study was to investigate the neural correlates of perceptual decisions in the context of emotional perception. To probe this question, we investigated how fluctuations in functional MRI (fMRI) signals were correlated with behavioral choice during a near-threshold fear detection task. fMRI signals predicted behavioral choice independently of stimulus properties and task accuracy in a network of brain regions linked to emotional processing: posterior cingulate cortex, medial prefrontal cortex, right inferior frontal gyrus, and left insula. We quantified the link between fMRI signals and behavioral choice in a whole-brain analysis by determining choice probabilities by means of signal-detection theory methods. Our results demonstrate that voxel-wise fMRI signals can reliably predict behavioral choice in a quantitative fashion (choice probabilities ranged from 0.63 to 0.78) at levels comparable to neuronal data. We suggest that the conscious decision that a fearful face has been seen is represented across a network of interconnected brain regions that prepare the organism to appropriately handle emotionally challenging stimuli and that regulate the associated emotional response. decision making | emotion | functional MRI

fMRI and MEG in the study of typical and atypical cognitive development.

PubMed

Taylor, M J; Donner, E J; Pang, E W

2012-01-01

The tremendous changes in brain structure over childhood are critical to the development of cognitive functions. Neuroimaging provides a means of linking these brain-behaviour relations, as task protocols can be adapted for use with young children to assess the development of cognitive functions in both typical and atypical populations. This paper reviews some of our research using magnetoencephalography (MEG) and functional MRI (fMRI) in the study of cognitive development, with a focus on frontal lobe functions. Working memory for complex abstract patterns showed clear development in terms of the recruitment of frontal regions, seen with fMRI, with indications of strategy differences across the age range, from 6 to 35 years of age. Right hippocampal involvement was also evident in these n-back tasks, demonstrating its involvement in recognition in simple working memory protocols. Children born very preterm (7 to 9 years of age) showed reduced fMRI activation particularly in the precuneus and right hippocampal regions relative to control children. In a large normative n-back study (n=90) with upright and inverted faces, MEG data also showed right hippocampal activation that was present across the age range; frontal sources were evident only from 10 years of age. Other studies have investigated the development of set shifting, an executive function that is often deficit in atypical populations. fMRI showed recruitment of frontal areas, including the insula, that have significantly different patterns in children (7 to 14 years of age) with autism spectrum disorder compared to typically developing children, indicating that successful performance implicated differing strategies in these two groups of children. These types of studies will help our understanding of both normal brain-behaviour development and cognitive dysfunction in atypically developing populations. Copyright © 2011 Elsevier Masson SAS. All rights reserved.

Bayesian spatiotemporal model of fMRI data using transfer functions.

PubMed

Quirós, Alicia; Diez, Raquel Montes; Wilson, Simon P

2010-09-01

This research describes a new Bayesian spatiotemporal model to analyse BOLD fMRI studies. In the temporal dimension, we describe the shape of the hemodynamic response function (HRF) with a transfer function model. The spatial continuity and local homogeneity of the evoked responses are modelled by a Gaussian Markov random field prior on the parameter indicating activations. The proposal constitutes an extension of the spatiotemporal model presented in a previous approach [Quirós, A., Montes Diez, R. and Gamerman, D., 2010. Bayesian spatiotemporal model of fMRI data, Neuroimage, 49: 442-456], offering more flexibility in the estimation of the HRF and computational advantages in the resulting MCMC algorithm. Simulations from the model are performed in order to ascertain the performance of the sampling scheme and the ability of the posterior to estimate model parameters, as well as to check the model sensitivity to signal to noise ratio. Results are shown on synthetic data and on a real data set from a block-design fMRI experiment. Copyright (c) 2010 Elsevier Inc. All rights reserved.

Identifying Autism from Resting-State fMRI Using Long Short-Term Memory Networks.

PubMed

Dvornek, Nicha C; Ventola, Pamela; Pelphrey, Kevin A; Duncan, James S

2017-09-01

Functional magnetic resonance imaging (fMRI) has helped characterize the pathophysiology of autism spectrum disorders (ASD) and carries promise for producing objective biomarkers for ASD. Recent work has focused on deriving ASD biomarkers from resting-state functional connectivity measures. However, current efforts that have identified ASD with high accuracy were limited to homogeneous, small datasets, while classification results for heterogeneous, multi-site data have shown much lower accuracy. In this paper, we propose the use of recurrent neural networks with long short-term memory (LSTMs) for classification of individuals with ASD and typical controls directly from the resting-state fMRI time-series. We used the entire large, multi-site Autism Brain Imaging Data Exchange (ABIDE) I dataset for training and testing the LSTM models. Under a cross-validation framework, we achieved classification accuracy of 68.5%, which is 9% higher than previously reported methods that used fMRI data from the whole ABIDE cohort. Finally, we presented interpretation of the trained LSTM weights, which highlight potential functional networks and regions that are known to be implicated in ASD.

Identifying Autism from Resting-State fMRI Using Long Short-Term Memory Networks

PubMed Central

Dvornek, Nicha C.; Ventola, Pamela; Pelphrey, Kevin A.; Duncan, James S.

2017-01-01

Functional magnetic resonance imaging (fMRI) has helped characterize the pathophysiology of autism spectrum disorders (ASD) and carries promise for producing objective biomarkers for ASD. Recent work has focused on deriving ASD biomarkers from resting-state functional connectivity measures. However, current efforts that have identified ASD with high accuracy were limited to homogeneous, small datasets, while classification results for heterogeneous, multi-site data have shown much lower accuracy. In this paper, we propose the use of recurrent neural networks with long short-term memory (LSTMs) for classification of individuals with ASD and typical controls directly from the resting-state fMRI time-series. We used the entire large, multi-site Autism Brain Imaging Data Exchange (ABIDE) I dataset for training and testing the LSTM models. Under a cross-validation framework, we achieved classification accuracy of 68.5%, which is 9% higher than previously reported methods that used fMRI data from the whole ABIDE cohort. Finally, we presented interpretation of the trained LSTM weights, which highlight potential functional networks and regions that are known to be implicated in ASD. PMID:29104967

Functional versus Nonfunctional Rehabilitation in Chronic Ischemic Stroke: Evidences from a Randomized Functional MRI Study

PubMed Central

Pelicioni, Maristela C. X.; Novaes, Morgana M.; Peres, Andre S. C.; Lino de Souza, Altay A.; Minelli, Cesar; Fabio, Soraia R. C.; Pontes-Neto, Octavio M.; Santos, Antonio C.; de Araujo, Draulio B.

2016-01-01

Motor rehabilitation of stroke survivors may include functional and/or nonfunctional strategy. The present study aimed to compare the effect of these two rehabilitation strategies by means of clinical scales and functional Magnetic Resonance Imaging (fMRI). Twelve hemiparetic chronic stroke patients were selected. Patients were randomly assigned a nonfunctional (NFS) or functional (FS) rehabilitation scheme. Clinical scales (Fugl-Meyer, ARA test, and modified Barthel) and fMRI were applied at four moments: before rehabilitation (P1) and immediately after (P2), 1 month after (P3), and three months after (P4) the end of rehabilitation. The NFS group improved significantly and exclusively their Fugl-Meyer scores at P2, P3, and P4, when compared to P1. On the other hand, the FS group increased significantly in Fugl-Meyer at P2, when compared to P1, and also in their ARA and Barthel scores. fMRI inspection at the individual level revealed that both rehabilitation schemes most often led to decreased activation sparseness, decreased activity of contralesional M1, increased asymmetry of M1 activity to the ipsilesional side, decreased perilesional activity, and decreased SMA activity. Increased M1 asymmetry with rehabilitation was also confirmed by Lateralization Indexes. Our clinical analysis revealed subtle differences between FS and NFS. PMID:26839716

An empirical comparison of SPM preprocessing parameters to the analysis of fMRI data.

PubMed

Della-Maggiore, Valeria; Chau, Wilkin; Peres-Neto, Pedro R; McIntosh, Anthony R

2002-09-01

We present the results from two sets of Monte Carlo simulations aimed at evaluating the robustness of some preprocessing parameters of SPM99 for the analysis of functional magnetic resonance imaging (fMRI). Statistical robustness was estimated by implementing parametric and nonparametric simulation approaches based on the images obtained from an event-related fMRI experiment. Simulated datasets were tested for combinations of the following parameters: basis function, global scaling, low-pass filter, high-pass filter and autoregressive modeling of serial autocorrelation. Based on single-subject SPM analysis, we derived the following conclusions that may serve as a guide for initial analysis of fMRI data using SPM99: (1) The canonical hemodynamic response function is a more reliable basis function to model the fMRI time series than HRF with time derivative. (2) Global scaling should be avoided since it may significantly decrease the power depending on the experimental design. (3) The use of a high-pass filter may be beneficial for event-related designs with fixed interstimulus intervals. (4) When dealing with fMRI time series with short interstimulus intervals (<8 s), the use of first-order autoregressive model is recommended over a low-pass filter (HRF) because it reduces the risk of inferential bias while providing a relatively good power. For datasets with interstimulus intervals longer than 8 seconds, temporal smoothing is not recommended since it decreases power. While the generalizability of our results may be limited, the methods we employed can be easily implemented by other scientists to determine the best parameter combination to analyze their data.

Extracting Visual Evoked Potentials from EEG Data Recorded During fMRI-guided Transcranial Magnetic Stimulation

PubMed Central

Sadeh, Boaz; Yovel, Galit

2014-01-01

Transcranial Magnetic Stimulation (TMS) is an effective method for establishing a causal link between a cortical area and cognitive/neurophysiological effects. Specifically, by creating a transient interference with the normal activity of a target region and measuring changes in an electrophysiological signal, we can establish a causal link between the stimulated brain area or network and the electrophysiological signal that we record. If target brain areas are functionally defined with prior fMRI scan, TMS could be used to link the fMRI activations with evoked potentials recorded. However, conducting such experiments presents significant technical challenges given the high amplitude artifacts introduced into the EEG signal by the magnetic pulse, and the difficulty to successfully target areas that were functionally defined by fMRI. Here we describe a methodology for combining these three common tools: TMS, EEG, and fMRI. We explain how to guide the stimulator's coil to the desired target area using anatomical or functional MRI data, how to record EEG during concurrent TMS, how to design an ERP study suitable for EEG-TMS combination and how to extract reliable ERP from the recorded data. We will provide representative results from a previously published study, in which fMRI-guided TMS was used concurrently with EEG to show that the face-selective N1 and the body-selective N1 component of the ERP are associated with distinct neural networks in extrastriate cortex. This method allows us to combine the high spatial resolution of fMRI with the high temporal resolution of TMS and EEG and therefore obtain a comprehensive understanding of the neural basis of various cognitive processes. PMID:24893706

Tract-based Spatial Statistics and fMRI Analysis in Patients with Small Cell Lung Cancer before Prophylactic Cranial Irradiation

NASA Astrophysics Data System (ADS)

Benezi, S.; Bromis, K.; Karavasilis, E.; Karanasiou, I. S.; Koutsoupidou, M.; Matsopoulos, G.; Ventouras, E.; Uzunoglu, N.; Kouloulias, V.; Papathanasiou, M.; Foteineas, A.; Efstathopoulos, E.; Kelekis, N.; Kelekis, D.

2015-09-01

Prophylactic cranial irradiation (PCI) is known to increase life expectancy to a significant degree in Small Cell Lung Cancer (SCLC) patients. The overall scope of this research is to investigate changes in structural and functional connectivity between SCLC patients and controls before and after PCI treatment. In the current study specifically we use diffusion tensor imaging (DTI) and functional Magnetic Resonance (fMRI) to identify potential alterations in white matter structure and brain function respectively, in SCLC patients before PCI compared to healthy participants. The results in DTI analysis have showed lower fractional anisotropy (FA) and higher eigenvalues in white matter regions in the patient group. Similarly, in fMRI analysis a lower level of activation in the primary somatosensory cortex was reported. The results presented herein are subject to further investigation with larger patient and control groups.

Gas Phase UTE MRI of Propane and Propene

PubMed Central

Kovtunov, Kirill V.; Romanov, Alexey S.; Salnikov, Oleg G.; Barskiy, Danila A.; Chekmenev, Eduard Y.; Koptyug, Igor V.

2016-01-01

1H MRI of gases can potentially enable functional lung imaging to probe gas ventilation and other functions. In this work, 1H MR images of hyperpolarized and thermally polarized propane gas were obtained using UTE (ultrashort echo time) pulse sequence. A 2D image of thermally polarized propane gas with ~0.9×0.9 mm2 spatial resolution was obtained in less than 2 seconds, demonstrating that even non-hyperpolarized hydrocarbon gases can be successfully utilized for conventional proton MRI. The experiments were also performed with hyperpolarized propane gas and demonstrated acquisition of high-resolution multi-slice FLASH 2D images in ca. 510 s and non slice-selective 2D UTE MRI images in ca. 2 s. The UTE approach adopted in this study can be potentially used for medical lung imaging. Furthermore, the possibility to combine UTE with selective suppression of 1H signals from one of the two gases in a mixture is demonstrated in this MRI study. The latter can be useful for visualizing industrially important processes where several gases may be present, e.g., gas-solid catalytic reactions. PMID:27478870

A Set of Functional Brain Networks for the Comprehensive Evaluation of Human Characteristics.

PubMed

Sung, Yul-Wan; Kawachi, Yousuke; Choi, Uk-Su; Kang, Daehun; Abe, Chihiro; Otomo, Yuki; Ogawa, Seiji

2018-01-01

Many human characteristics must be evaluated to comprehensively understand an individual, and measurements of the corresponding cognition/behavior are required. Brain imaging by functional MRI (fMRI) has been widely used to examine brain function related to human cognition/behavior. However, few aspects of cognition/behavior of individuals or experimental groups can be examined through task-based fMRI. Recently, resting state fMRI (rs-fMRI) signals have been shown to represent functional infrastructure in the brain that is highly involved in processing information related to cognition/behavior. Using rs-fMRI may allow diverse information about the brain through a single MRI scan to be obtained, as rs-fMRI does not require stimulus tasks. In this study, we attempted to identify a set of functional networks representing cognition/behavior that are related to a wide variety of human characteristics and to evaluate these characteristics using rs-fMRI data. If possible, these findings would support the potential of rs-fMRI to provide diverse information about the brain. We used resting-state fMRI and a set of 130 psychometric parameters that cover most human characteristics, including those related to intelligence and emotional quotients and social ability/skill. We identified 163 brain regions by VBM analysis using regression analysis with 130 psychometric parameters. Next, using a 163 × 163 correlation matrix, we identified functional networks related to 111 of the 130 psychometric parameters. Finally, we made an 8-class support vector machine classifiers corresponding to these 111 functional networks. Our results demonstrate that rs-fMRI signals contain intrinsic information about brain function related to cognition/behaviors and that this set of 111 networks/classifiers can be used to comprehensively evaluate human characteristics.

Is Broca's Area Involved in the Processing of Passive Sentences? An Event-Related fMRI Study

ERIC Educational Resources Information Center

Yokoyama, Satoru; Watanabe, Jobu; Iwata, Kazuki; Ikuta, Naho; Haji, Tomoki; Usui, Nobuo; Taira, Masato; Miyamoto, Tadao; Nakamura, Wataru; Sato, Shigeru; Horie, Kaoru; Kawashima, Ryuta

2007-01-01

We used functional magnetic resonance imaging (fMRI) to investigate whether activation in Broca's area is greater during the processing of passive versus active sentences in the brains of healthy subjects. Twenty Japanese native speakers performed a visual sentence comprehension task in which they were asked to read a visually presented sentence…

When We like What We Know--A Parametric fMRI Analysis of Beauty and Familiarity

ERIC Educational Resources Information Center

Bohrn, Isabel C.; Altmann, Ulrike; Lubrich, Oliver; Menninghaus, Winfried; Jacobs, Arthur M.

2013-01-01

This paper presents a neuroscientific study of aesthetic judgments on written texts. In an fMRI experiment participants read a number of proverbs without explicitly evaluating them. In a post-scan rating they rated each item for familiarity and beauty. These individual ratings were correlated with the functional data to investigate the neural…

A wavelet-based statistical analysis of FMRI data: I. motivation and data distribution modeling.

PubMed

Dinov, Ivo D; Boscardin, John W; Mega, Michael S; Sowell, Elizabeth L; Toga, Arthur W

2005-01-01

We propose a new method for statistical analysis of functional magnetic resonance imaging (fMRI) data. The discrete wavelet transformation is employed as a tool for efficient and robust signal representation. We use structural magnetic resonance imaging (MRI) and fMRI to empirically estimate the distribution of the wavelet coefficients of the data both across individuals and spatial locations. An anatomical subvolume probabilistic atlas is used to tessellate the structural and functional signals into smaller regions each of which is processed separately. A frequency-adaptive wavelet shrinkage scheme is employed to obtain essentially optimal estimations of the signals in the wavelet space. The empirical distributions of the signals on all the regions are computed in a compressed wavelet space. These are modeled by heavy-tail distributions because their histograms exhibit slower tail decay than the Gaussian. We discovered that the Cauchy, Bessel K Forms, and Pareto distributions provide the most accurate asymptotic models for the distribution of the wavelet coefficients of the data. Finally, we propose a new model for statistical analysis of functional MRI data using this atlas-based wavelet space representation. In the second part of our investigation, we will apply this technique to analyze a large fMRI dataset involving repeated presentation of sensory-motor response stimuli in young, elderly, and demented subjects.

A receptor-based model for dopamine-induced fMRI signal

PubMed Central

Mandeville, Joseph. B.; Sander, Christin Y. M.; Jenkins, Bruce G.; Hooker, Jacob M.; Catana, Ciprian; Vanduffel, Wim; Alpert, Nathaniel M.; Rosen, Bruce R.; Normandin, Marc D.

2013-01-01

This report describes a multi-receptor physiological model of the fMRI temporal response and signal magnitude evoked by drugs that elevate synaptic dopamine in basal ganglia. The model is formulated as a summation of dopamine’s effects at D1-like and D2-like receptor families, which produce functional excitation and inhibition, respectively, as measured by molecular indicators like adenylate cyclase or neuroimaging techniques like fMRI. Functional effects within the model are described in terms of relative changes in receptor occupancies scaled by receptor densities and neuro-vascular coupling constants. Using literature parameters, the model reconciles many discrepant observations and interpretations of pre-clinical data. Additionally, we present data showing that amphetamine stimulation produces fMRI inhibition at low doses and a biphasic response at higher doses in the basal ganglia of non-human primates (NHP), in agreement with model predictions based upon the respective levels of evoked dopamine. Because information about dopamine release is required to inform the fMRI model, we simultaneously acquired PET 11C-raclopride data in several studies to evaluate the relationship between raclopride displacement and assumptions about dopamine release. At high levels of dopamine release, results suggest that refinements of the model will be required to consistently describe the PET and fMRI data. Overall, the remarkable success of the model in describing a wide range of preclinical fMRI data indicate that this approach will be useful for guiding the design and analysis of basic science and clinical investigations and for interpreting the functional consequences of dopaminergic stimulation in normal subjects and in populations with dopaminergic neuroadaptations. PMID:23466936

Advances in the application of MRI to amyotrophic lateral sclerosis

PubMed Central

Turner, Martin R; Modo, Michel

2011-01-01

Importance of the field With the emergence of therapeutic candidates for the incurable and rapidly progressive neurodegenerative condition of amyotrophic lateral sclerosis (ALS), it will be essential to develop easily obtainable biomarkers for diagnosis, as well as monitoring, in a disease where clinical examination remains the predominant diagnostic tool. Magnetic resonance imaging (MRI) has greatly developed over the past thirty years since its initial introduction to neuroscience. With multi-modal applications, MRI is now offering exciting opportunities to develop practical biomarkers in ALS. Areas covered in this review The historical application of MRI to the field of ALS, its state-of-the-art and future aspirations will be reviewed. Specifically, the significance and limitations of structural MRI to detect gross morphological tissue changes in relation to clinical presentation will be discussed. The more recent application of diffusion tensor imaging (DTI), magnetic resonance spectroscopy (MRS), functional and resting-state MRI (fMRI & R-fMRI) will be contrasted in relation to these more conventional MRI assessments. Finally, future aspirations will be sketched out in providing a more disease mechanism-based molecular MRI. What the reader will gain This review will equip the reader with an overview of the application of MRI to ALS and illustrate its potential to develop biomarkers. This discussion is exemplified by key studies, demonstrating the strengths and limitations of each modality. The reader will gain an expert opinion on both the current and future developments of MR imaging in ALS. Take home message MR imaging generates potential diagnostic, prognostic and therapeutic monitoring biomarkers of ALS. The emerging fusion of structural, functional and potentially molecular imaging will improve our understanding of wider cerebral connectivity and holds the promise of biomarkers sensitive to the earliest changes. PMID:21516259

Towards neural correlates of auditory stimulus processing: A simultaneous auditory evoked potentials and functional magnetic resonance study using an odd-ball paradigm

PubMed Central

Milner, Rafał; Rusiniak, Mateusz; Lewandowska, Monika; Wolak, Tomasz; Ganc, Małgorzata; Piątkowska-Janko, Ewa; Bogorodzki, Piotr; Skarżyński, Henryk

2014-01-01

Background The neural underpinnings of auditory information processing have often been investigated using the odd-ball paradigm, in which infrequent sounds (deviants) are presented within a regular train of frequent stimuli (standards). Traditionally, this paradigm has been applied using either high temporal resolution (EEG) or high spatial resolution (fMRI, PET). However, used separately, these techniques cannot provide information on both the location and time course of particular neural processes. The goal of this study was to investigate the neural correlates of auditory processes with a fine spatio-temporal resolution. A simultaneous auditory evoked potentials (AEP) and functional magnetic resonance imaging (fMRI) technique (AEP-fMRI), together with an odd-ball paradigm, were used. Material/Methods Six healthy volunteers, aged 20–35 years, participated in an odd-ball simultaneous AEP-fMRI experiment. AEP in response to acoustic stimuli were used to model bioelectric intracerebral generators, and electrophysiological results were integrated with fMRI data. Results fMRI activation evoked by standard stimuli was found to occur mainly in the primary auditory cortex. Activity in these regions overlapped with intracerebral bioelectric sources (dipoles) of the N1 component. Dipoles of the N1/P2 complex in response to standard stimuli were also found in the auditory pathway between the thalamus and the auditory cortex. Deviant stimuli induced fMRI activity in the anterior cingulate gyrus, insula, and parietal lobes. Conclusions The present study showed that neural processes evoked by standard stimuli occur predominantly in subcortical and cortical structures of the auditory pathway. Deviants activate areas non-specific for auditory information processing. PMID:24413019

Efficient solution methodology for calibrating the hemodynamic model using functional Magnetic Resonance Imaging (fMRI) measurements.

PubMed

Zambri, Brian; Djellouli, Rabia; Laleg-Kirati, Taous-Meriem

2015-08-01

Our aim is to propose a numerical strategy for retrieving accurately and efficiently the biophysiological parameters as well as the external stimulus characteristics corresponding to the hemodynamic mathematical model that describes changes in blood flow and blood oxygenation during brain activation. The proposed method employs the TNM-CKF method developed in [1], but in a prediction/correction framework. We present numerical results using both real and synthetic functional Magnetic Resonance Imaging (fMRI) measurements to highlight the performance characteristics of this computational methodology.

Three-dimensional functional magnetic resonance imaging of human brain on a clinical 1.5-T scanner.

PubMed Central

van Gelderen, P; Ramsey, N F; Liu, G; Duyn, J H; Frank, J A; Weinberger, D R; Moonen, C T

1995-01-01

Functional magnetic resonance imaging (fMRI) is a tool for mapping brain function that utilizes neuronal activity-induced changes in blood oxygenation. An efficient three-dimensional fMRI method is presented for imaging brain activity on conventional, widely available, 1.5-T scanners, without additional hardware. This approach uses large magnetic susceptibility weighting based on the echo-shifting principle combined with multiple gradient echoes per excitation. Motor stimulation, induced by self-paced finger tapping, reliably produced significant signal increase in the hand region of the contralateral primary motor cortex in every subject tested. Images Fig. 2 Fig. 3 PMID:7624341

The clinical outcomes of deep gray matter injury in children with cerebral palsy in relation with brain magnetic resonance imaging.

PubMed

Choi, Ja Young; Choi, Yoon Seong; Rha, Dong-Wook; Park, Eun Sook

2016-08-01

In the present study we investigated the nature and extent of clinical outcomes using various classifications and analyzed the relationship between brain magnetic resonance imaging (MRI) findings and the extent of clinical outcomes in children with cerebral palsy (CP) with deep gray matter injury. The deep gray matter injuries of 69 children were classified into hypoxic ischemic encephalopathy (HIE) and kernicterus patterns. HIE patterns were divided into four groups (I-IV) based on severity. Functional classification was investigated using the gross motor function classification system-expanded and revised, manual ability classification system, communication function classification system, and tests of cognitive function, and other associated problems. The severity of HIE pattern on brain MRI was strongly correlated with the severity of clinical outcomes in these various domains. Children with a kernicterus pattern showed a wide range of clinical outcomes in these areas. Children with severe HIE are at high risk of intellectual disability (ID) or epilepsy and children with a kernicterus pattern are at risk of hearing impairment and/or ID. Grading severity of HIE pattern on brain MRI is useful for predicting overall outcomes. The clinical outcomes of children with a kernicterus pattern range widely from mild to severe. Delineation of the clinical outcomes of children with deep gray matter injury, which are a common abnormal brain MRI finding in children with CP, is necessary. The present study provides clinical outcomes for various domains in children with deep gray matter injury on brain MRI. The deep gray matter injuries were divided into two major groups; HIE and kernicterus patterns. Our study showed that severity of HIE pattern on brain MRI was strongly associated with the severity of impairments in gross motor function, manual ability, communication function, and cognition. These findings suggest that severity of HIE pattern can be useful for predicting the severity of impairments. Conversely, children with a kernicterus pattern showed a wide range of clinical outcomes in various domains. Children with severe HIE pattern are at high risk of ID or epilepsy and children with kernicterus pattern are at risk of hearing impairment or ID. The strength of our study was the assessment of clinical outcomes after 3 years of age using standardized classification systems in various domains in children with deep gray matter injury. Copyright © 2016 Elsevier Ltd. All rights reserved.

Errors on interrupter tasks presented during spatial and verbal working memory performance are linearly linked to large-scale functional network connectivity in high temporal resolution resting state fMRI.

PubMed

Magnuson, Matthew Evan; Thompson, Garth John; Schwarb, Hillary; Pan, Wen-Ju; McKinley, Andy; Schumacher, Eric H; Keilholz, Shella Dawn

2015-12-01

The brain is organized into networks composed of spatially separated anatomical regions exhibiting coherent functional activity over time. Two of these networks (the default mode network, DMN, and the task positive network, TPN) have been implicated in the performance of a number of cognitive tasks. To directly examine the stable relationship between network connectivity and behavioral performance, high temporal resolution functional magnetic resonance imaging (fMRI) data were collected during the resting state, and behavioral data were collected from 15 subjects on different days, exploring verbal working memory, spatial working memory, and fluid intelligence. Sustained attention performance was also evaluated in a task interleaved between resting state scans. Functional connectivity within and between the DMN and TPN was related to performance on these tasks. Decreased TPN resting state connectivity was found to significantly correlate with fewer errors on an interrupter task presented during a spatial working memory paradigm and decreased DMN/TPN anti-correlation was significantly correlated with fewer errors on an interrupter task presented during a verbal working memory paradigm. A trend for increased DMN resting state connectivity to correlate to measures of fluid intelligence was also observed. These results provide additional evidence of the relationship between resting state networks and behavioral performance, and show that such results can be observed with high temporal resolution fMRI. Because cognitive scores and functional connectivity were collected on nonconsecutive days, these results highlight the stability of functional connectivity/cognitive performance coupling.

Application of fractal dimension method of functional MRI time-series to limbic dysregulation in anxiety study.

PubMed

Olejarczyk, Elzbieta

2007-01-01

Functional magnetic resonance imaging (fMRI) allows to investigate the amplitude of activation in neural networks of brain. In this work we present the results of fMRI time-series analysis performed to identify the process of dysregulation of dynamic interaction between different limbic system regions in healthy adults in state of increased anxiety. The results obtain for 65 healthy adults using nonlinear dynamics methods like fractal dimension confirm the key roles of the bilateral amygdala, bilateral hippocampus, BA9 (dorsolateral prefrontal cortex), and BA45 (ventromedial prefrontal cortex) in modulating emotional response in healthy adults. For different regions of interest (ROIs) significant correlations were found not only for the neutral respective rest but also for fear and angry contrasts.

Comparing diffuse optical tomography and functional magnetic resonance imaging signals during a cognitive task: pilot study

PubMed Central

Hernández-Martin, Estefania; Marcano, Francisco; Casanova, Oscar; Modroño, Cristian; Plata-Bello, Julio; González-Mora, Jose Luis

2017-01-01

Abstract. Diffuse optical tomography (DOT) measures concentration changes in both oxy- and deoxyhemoglobin providing three-dimensional images of local brain activations. A pilot study, which compares both DOT and functional magnetic resonance imaging (fMRI) volumes through t-maps given by canonical statistical parametric mapping (SPM) processing for both data modalities, is presented. The DOT series were processed using a method that is based on a Bayesian filter application on raw DOT data to remove physiological changes and minimum description length application index to select a number of singular values, which reduce the data dimensionality during image reconstruction and adaptation of DOT volume series to normalized standard space. Therefore, statistical analysis is performed with canonical SPM software in the same way as fMRI analysis is done, accepting DOT volumes as if they were fMRI volumes. The results show the reproducibility and ruggedness of the method to process DOT series on group analysis using cognitive paradigms on the prefrontal cortex. Difficulties such as the fact that scalp–brain distances vary between subjects or cerebral activations are difficult to reproduce due to strategies used by the subjects to solve arithmetic problems are considered. T-images given by fMRI and DOT volume series analyzed in SPM show that at the functional level, both DOT and fMRI measures detect the same areas, although DOT provides complementary information to fMRI signals about cerebral activity. PMID:28386575

An fMRI study of somatosensory-implicated acupuncture points in stable somatosensory stroke patients.

PubMed

Li, Geng; Jack, Clifford R; Yang, Edward S

2006-11-01

To assess differences in brain responses between stroke patients and controls to tactile and electrical acupuncture stimulation using functional MRI (fMRI). A total of 12 male, clinically stable stroke patients with left side somatosensory deficits, and 12 age-matched male control subjects were studied. fMRI was performed with two different paradigms; namely, tactile stimuli and electrical stimulation at acupuncture points LI4 and LI11 on the affected side of the body. fMRI data were analyzed using SPM99. Tactile stimulation in both patients and controls produced significant activation in primary and secondary sensory and motor cortical areas and cerebellum. Greater activation was present in patients than controls in the somatosensory cortex with both the tactile task and the acupuncture point (acupoint) stimulation. Activation was greater during the tactile task than the acupuncture stimulation in patients and normal controls. Differences observed between patients and controls on both tasks may indicate compensatory over recruitment of neocortical areas involved in somatosensory perception in the stroke patients. The observed differences between patients and controls on the acupoint stimulation task may also indicate that stimulation of acupoints used therapeutically to enhance recovery from stroke, selectively activates areas thought to be involved in mediating recovery from stroke via functional plasticity. fMRI of acupoint stimulation may illustrate the functional substrate of the therapeutically beneficial effect of acupuncture in stroke rehabilitation. Copyright (c) 2006 Wiley-Liss, Inc.

The role of magnetic resonance imaging techniques in evaluation and management of the idiopathic inflammatory myopathies.

PubMed

Day, Jessica; Patel, Sandy; Limaye, Vidya

2017-04-01

Magnetic resonance imaging (MRI) is an important tool in the evaluation of neuromuscular disorders. MRI accurately demonstrates muscle oedema, atrophy, subcutaneous pathology and fatty infiltration and also highlights the distribution of muscle involvement. This review examines the role of MRI in evaluation of the idiopathic inflammatory myopathies (IIMs), a heterogeneous group of autoimmune conditions characterised by muscle inflammation and a variety of extra-muscular manifestations. MRI has a clear role in aiding diagnosis of these conditions, guiding muscle biopsy, differentiating subtypes of IIM using a pattern-based approach, and monitoring disease activity in a longitudinal fashion. Whole body MRI is an emerging technique that offers several advantages over regional MRI, but is not currently widely available. We will also consider newer MRI techniques which provide detailed information regarding the metabolism, function and structure of muscle, although their use is restricted to research purposes at present. Copyright © 2017 Elsevier Inc. All rights reserved.

Subtle In-Scanner Motion Biases Automated Measurement of Brain Anatomy From In Vivo MRI

PubMed Central

Alexander-Bloch, Aaron; Clasen, Liv; Stockman, Michael; Ronan, Lisa; Lalonde, Francois; Giedd, Jay; Raznahan, Armin

2016-01-01

While the potential for small amounts of motion in functional magnetic resonance imaging (fMRI) scans to bias the results of functional neuroimaging studies is well appreciated, the impact of in-scanner motion on morphological analysis of structural MRI is relatively under-studied. Even among “good quality” structural scans, there may be systematic effects of motion on measures of brain morphometry. In the present study, the subjects’ tendency to move during fMRI scans, acquired in the same scanning sessions as their structural scans, yielded a reliable, continuous estimate of in-scanner motion. Using this approach within a sample of 127 children, adolescents, and young adults, significant relationships were found between this measure and estimates of cortical gray matter volume and mean curvature, as well as trend-level relationships with cortical thickness. Specifically, cortical volume and thickness decreased with greater motion, and mean curvature increased. These effects of subtle motion were anatomically heterogeneous, were present across different automated imaging pipelines, showed convergent validity with effects of frank motion assessed in a separate sample of 274 scans, and could be demonstrated in both pediatric and adult populations. Thus, using different motion assays in two large non-overlapping sets of structural MRI scans, convergent evidence showed that in-scanner motion—even at levels which do not manifest in visible motion artifact—can lead to systematic and regionally specific biases in anatomical estimation. These findings have special relevance to structural neuroimaging in developmental and clinical datasets, and inform ongoing efforts to optimize neuroanatomical analysis of existing and future structural MRI datasets in non-sedated humans. PMID:27004471

Working memory capacity and the functional connectome - insights from resting-state fMRI and voxelwise centrality mapping.

PubMed

Markett, Sebastian; Reuter, Martin; Heeren, Behrend; Lachmann, Bernd; Weber, Bernd; Montag, Christian

2018-02-01

The functional connectome represents a comprehensive network map of functional connectivity throughout the human brain. To date, the relationship between the organization of functional connectivity and cognitive performance measures is still poorly understood. In the present study we use resting-state functional magnetic resonance imaging (fMRI) data to explore the link between the functional connectome and working memory capacity in an individual differences design. Working memory capacity, which refers to the maximum amount of context information that an individual can retain in the absence of external stimulation, was assessed outside the MRI scanner and estimated based on behavioral data from a change detection task. Resting-state time series were analyzed by means of voxelwise degree and eigenvector centrality mapping, which are data-driven network analytic approaches for the characterization of functional connectivity. We found working memory capacity to be inversely correlated with both centrality in the right intraparietal sulcus. Exploratory analyses revealed that this relationship was putatively driven by an increase in negative connectivity strength of the structure. This resting-state connectivity finding fits previous task based activation studies that have shown that this area responds to manipulations of working memory load.

An Automated Method for Identifying Artifact in Independent Component Analysis of Resting-State fMRI

PubMed Central

Bhaganagarapu, Kaushik; Jackson, Graeme D.; Abbott, David F.

2013-01-01

An enduring issue with data-driven analysis and filtering methods is the interpretation of results. To assist, we present an automatic method for identification of artifact in independent components (ICs) derived from functional MRI (fMRI). The method was designed with the following features: does not require temporal information about an fMRI paradigm; does not require the user to train the algorithm; requires only the fMRI images (additional acquisition of anatomical imaging not required); is able to identify a high proportion of artifact-related ICs without removing components that are likely to be of neuronal origin; can be applied to resting-state fMRI; is automated, requiring minimal or no human intervention. We applied the method to a MELODIC probabilistic ICA of resting-state functional connectivity data acquired in 50 healthy control subjects, and compared the results to a blinded expert manual classification. The method identified between 26 and 72% of the components as artifact (mean 55%). About 0.3% of components identified as artifact were discordant with the manual classification; retrospective examination of these ICs suggested the automated method had correctly identified these as artifact. We have developed an effective automated method which removes a substantial number of unwanted noisy components in ICA analyses of resting-state fMRI data. Source code of our implementation of the method is available. PMID:23847511

Multimodal integration of fMRI and EEG data for high spatial and temporal resolution analysis of brain networks

PubMed Central

Mantini, D.; Marzetti, L.; Corbetta, M.; Romani, G.L.; Del Gratta, C.

2017-01-01

Two major non-invasive brain mapping techniques, electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), have complementary advantages with regard to their spatial and temporal resolution. We propose an approach based on the integration of EEG and fMRI, enabling the EEG temporal dynamics of information processing to be characterized within spatially well-defined fMRI large-scale networks. First, the fMRI data are decomposed into networks by means of spatial independent component analysis (sICA), and those associated with intrinsic activity and/or responding to task performance are selected using information from the related time-courses. Next, the EEG data over all sensors are averaged with respect to event timing, thus calculating event-related potentials (ERPs). The ERPs are subjected to temporal ICA (tICA), and the resulting components are localized with the weighted minimum norm (WMNLS) algorithm using the task-related fMRI networks as priors. Finally, the temporal contribution of each ERP component in the areas belonging to the fMRI large-scale networks is estimated. The proposed approach has been evaluated on visual target detection data. Our results confirm that two different components, commonly observed in EEG when presenting novel and salient stimuli respectively, are related to the neuronal activation in large-scale networks, operating at different latencies and associated with different functional processes. PMID:20052528

Functional Magnetic Resonance Imaging for Preoperative Planning in Brain Tumour Surgery.

PubMed

Lau, Jonathan C; Kosteniuk, Suzanne E; Bihari, Frank; Megyesi, Joseph F

2017-01-01

Functional magnetic resonance imaging (fMRI) is being increasingly used for the preoperative evaluation of patients with brain tumours. The study is a retrospective chart review investigating the use of clinical fMRI from 2002 through 2013 in the preoperative evaluation of brain tumour patients. Baseline demographic and clinical data were collected. The specific fMRI protocols used for each patient were recorded. Sixty patients were identified over the 12-year period. The tumour types most commonly investigated were high-grade glioma (World Health Organization grade III or IV), low-grade glioma (World Health Organization grade II), and meningioma. Most common presenting symptoms were seizures (69.6%), language deficits (23.2%), and headache (19.6%). There was a predominance of left hemispheric lesions investigated with fMRI (76.8% vs 23.2% for right). The most commonly involved lobes were frontal (64.3%), temporal (33.9%), parietal (21.4%), and insular (7.1%). The most common fMRI paradigms were language (83.9%), motor (75.0%), sensory (16.1%), and memory (10.7%). The majority of patients ultimately underwent a craniotomy (75.0%), whereas smaller groups underwent stereotactic biopsy (8.9%) and nonsurgical management (16.1%). Time from request for fMRI to actual fMRI acquisition was 3.1±2.3 weeks. Time from fMRI acquisition to intervention was 4.9±5.5 weeks. We have characterized patient demographics in a retrospective single-surgeon cohort undergoing preoperative clinical fMRI at a Canadian centre. Our experience suggests an acceptable wait time from scan request to scan completion/analysis and from scan to intervention.

Pulmonary 3 T MRI with ultrashort TEs: influence of ultrashort echo time interval on pulmonary functional and clinical stage assessments of smokers.

PubMed

Ohno, Yoshiharu; Nishio, Mizuho; Koyama, Hisanobu; Yoshikawa, Takeshi; Matsumoto, Sumiaki; Seki, Shinichiro; Obara, Makoto; van Cauteren, Marc; Takahashi, Masaya; Sugimura, Kazuro

2014-04-01

To assess the influence of ultrashort TE (UTE) intervals on pulmonary magnetic resonance imaging (MRI) with UTEs (UTE-MRI) for pulmonary functional loss assessment and clinical stage classification of smokers. A total 60 consecutive smokers (43 men and 17 women; mean age 70 years) with and without COPD underwent thin-section multidetector row computed tomography (MDCT), UTE-MRI, and pulmonary functional measurements. For each smoker, UTE-MRI was performed with three different UTE intervals (UTE-MRI A: 0.5 msec, UTE-MRI B: 1.0 msec, UTE-MRI C: 1.5 msec). By using the GOLD guidelines, the subjects were classified as: "smokers without COPD," "mild COPD," "moderate COPD," and "severe or very severe COPD." Then the mean T2* value from each UTE-MRI and CT-based functional lung volume (FLV) were correlated with pulmonary function test. Finally, Fisher's PLSD test was used to evaluate differences in each index among the four clinical stages. Each index correlated significantly with pulmonary function test results (P < 0.05). CT-based FLV and mean T2* values obtained from UTE-MRI A and B showed significant differences among all groups except between "smokers without COPD" and "mild COPD" groups (P < 0.05). UTE-MRI has a potential for management of smokers and the UTE interval is suggested as an important parameter in this setting. Copyright © 2013 Wiley Periodicals, Inc.

Exploring connectivity with large-scale Granger causality on resting-state functional MRI.

PubMed

DSouza, Adora M; Abidin, Anas Z; Leistritz, Lutz; Wismüller, Axel

2017-08-01

Large-scale Granger causality (lsGC) is a recently developed, resting-state functional MRI (fMRI) connectivity analysis approach that estimates multivariate voxel-resolution connectivity. Unlike most commonly used multivariate approaches, which establish coarse-resolution connectivity by aggregating voxel time-series avoiding an underdetermined problem, lsGC estimates voxel-resolution, fine-grained connectivity by incorporating an embedded dimension reduction. We investigate application of lsGC on realistic fMRI simulations, modeling smoothing of neuronal activity by the hemodynamic response function and repetition time (TR), and empirical resting-state fMRI data. Subsequently, functional subnetworks are extracted from lsGC connectivity measures for both datasets and validated quantitatively. We also provide guidelines to select lsGC free parameters. Results indicate that lsGC reliably recovers underlying network structure with area under receiver operator characteristic curve (AUC) of 0.93 at TR=1.5s for a 10-min session of fMRI simulations. Furthermore, subnetworks of closely interacting modules are recovered from the aforementioned lsGC networks. Results on empirical resting-state fMRI data demonstrate recovery of visual and motor cortex in close agreement with spatial maps obtained from (i) visuo-motor fMRI stimulation task-sequence (Accuracy=0.76) and (ii) independent component analysis (ICA) of resting-state fMRI (Accuracy=0.86). Compared with conventional Granger causality approach (AUC=0.75), lsGC produces better network recovery on fMRI simulations. Furthermore, it cannot recover functional subnetworks from empirical fMRI data, since quantifying voxel-resolution connectivity is not possible as consequence of encountering an underdetermined problem. Functional network recovery from fMRI data suggests that lsGC gives useful insight into connectivity patterns from resting-state fMRI at a multivariate voxel-resolution. Copyright © 2017 Elsevier B.V. All rights reserved.

Computer-controlled stimulation for functional magnetic resonance imaging studies of the neonatal olfactory system

PubMed Central

Arichi, T; Gordon-Williams, R; Allievi, A; Groves, AM; Burdet, E; Edwards, AD

2013-01-01

Aim Olfactory sensation is highly functional early in human neonatal life, with studies suggesting that odours can influence behaviour and infant–mother bonding. Due to its good spatial properties, blood oxygen level–dependent (BOLD) contrast functional magnetic resonance imaging (fMRI) has the potential to rapidly advance our understanding of the neural activity which underlies the development of olfactory perception in this key period. We aimed to design an ‘olfactometer’ specifically for use with neonatal subjects for fMRI studies of odour perception. Methods We describe a fully automated and programmable, fMRI compatible system capable of presenting odorant liquids. To prevent contamination of the system and minimize between-subject infective risk, the majority of the olfactometer is constructed from single-use, readily available clinical equipment. The system was used to present the odour of infant formula milk in a validation group of seven neonatal subjects at term equivalent postmenstrual age (median age 40 weeks). Results A safe, reliable and reproducible pattern of stimulation was delivered leading to well-localized positive BOLD functional responses in the piriform cortex, amygdala, thalamus, insular cortex and cerebellum. Conclusions The described system is therefore suitable for detailed studies of the ontology of olfactory sensation and perception during early human brain development. PMID:23789919

Biocytin-Derived MRI Contrast Agent for Longitudinal Brain Connectivity Studies

PubMed Central

2011-01-01

To investigate the connectivity of brain networks noninvasively and dynamically, we have developed a new strategy to functionalize neuronal tracers and designed a biocompatible probe that can be visualized in vivo using magnetic resonance imaging (MRI). Furthermore, the multimodal design used allows combined ex vivo studies with microscopic spatial resolution by conventional histochemical techniques. We present data on the functionalization of biocytin, a well-known neuronal tract tracer, and demonstrate the validity of the approach by showing brain networks of cortical connectivity in live rats under MRI, together with the corresponding microscopic details, such as fibers and neuronal morphology under light microscopy. We further demonstrate that the developed molecule is the first MRI-visible probe to preferentially trace retrograde connections. Our study offers a new platform for the development of multimodal molecular imaging tools of broad interest in neuroscience, that capture in vivo the dynamics of large scale neural networks together with their microscopic characteristics, thereby spanning several organizational levels. PMID:22860157

Influence of neurobehavioral incentive valence and magnitude on alcohol drinking behavior

PubMed Central

Joseph, Jane E.; Zhu, Xun; Corbly, Christine R.; DeSantis, Stacia; Lee, Dustin C.; Baik, Grace; Kiser, Seth; Jiang, Yang; Lynam, Donald R.; Kelly, Thomas H.

2014-01-01

The monetary incentive delay (MID) task is a widely used probe for isolating neural circuitry in the human brain associated with incentive motivation. In the present functional magnetic resonance imaging (fMRI) study, 82 young adults, characterized along dimensions of impulsive sensation seeking, completed a MID task. fMRI and behavioral incentive functions were decomposed into incentive valence and magnitude parameters, which were used as predictors in linear regression to determine whether mesolimbic response is associated with problem drinking and recent alcohol use. Alcohol use was best explained by higher fMRI response to anticipation of losses and feedback on high gains in the thalamus. In contrast, problem drinking was best explained by reduced sensitivity to large incentive values in meso-limbic regions in the anticipation phase and increased sensitivity to small incentive values in the dorsal caudate nucleus in the feedback phase. Altered fMRI responses to monetary incentives in mesolimbic circuitry, particularly those alterations associated with problem drinking, may serve as potential early indicators of substance abuse trajectories. PMID:25261001

Transcortical Sensory Aphasia after Left Frontal Lobe Infarction: Loss of Functional Connectivity.

PubMed

Kwon, Miseon; Shim, Woo Hyun; Kim, Sang-Joon; Kim, Jong S

2017-01-01

The underlying mechanism of transcortical sensory aphasia (TSA) caused by lesions occurring in the left frontal lobe remains unclear. We attempted to investigate the mechanism with the use of functional MRI (fMRI). We studied 2 patients with TSA after a left frontal infarction identified by diffusion-weighted MRI. As control subjects, a patient with transcortical motor aphasia and a healthy normal adult were chosen. The Korean version of Western Aphasia Battery was performed initially and at 3 months post stroke. We performed fMRI using verb generation and sentence completion tasks. Resting-state fMRI (rs-fMRI) was also obtained for network-level analysis initially and at 3 months post stroke. The results of diffusion- and perfusion-weighted MRI revealed no diffusion-perfusion mismatch. Initial fMRI in patients with TSA showed no reversed inter-/intrahemispheric activation patterns. rs-fMRI showed significantly decreased resting-state functional connectivity in the language network in patients with TSA compared with the control subjects. Follow-up rs-fMRI studies showed improvement in functional connectivity along with the recovery of patients' language function. Our data showed that the auditory comprehension deficits in patients with frontal lobe infarcts is attributed to difficulty accessing the posterior language area due to functional disconnection between language centers in the acute stage of stroke. © 2017 S. Karger AG, Basel.

Cortical and subcortical mapping of language areas: correlation of functional MRI and tractography in a 3T scanner with intraoperative cortical and subcortical stimulation in patients with brain tumors located in eloquent areas.

PubMed

Jiménez de la Peña, M; Gil Robles, S; Recio Rodríguez, M; Ruiz Ocaña, C; Martínez de Vega, V

2013-01-01

To describe the detection of cortical areas and subcortical pathways involved in language observed in MRI activation studies and tractography in a 3T MRI scanner and to correlate the findings of these functional studies with direct intraoperative cortical and subcortical stimulation. We present a series of 14 patients with focal brain tumors adjacent to eloquent brain areas. All patients underwent neuropsychological evaluation before and after surgery. All patients underwent MRI examination including structural sequences, perfusion imaging, spectroscopy, functional imaging to determine activation of motor and language areas, and 3D tractography. All patients underwent cortical mapping through cortical and subcortical stimulation during the operation to resect the tumor. Postoperative follow-up studies were done 24 hours after surgery. The correlation of motor function and of the corticospinal tract determined by functional MRI and tractography with intraoperative mapping of cortical and subcortical motor areas was complete. The eloquent brain areas of language expression and reception were strongly correlated with intraoperative cortical mapping in all but two cases (a high grade infiltrating glioma and a low grade glioma located in the frontal lobe). 3D tractography identified the arcuate fasciculus, the lateral part of the superior longitudinal fasciculus, the subcallosal fasciculus, the inferior fronto-occipital fasciculus, and the optic radiations, which made it possible to mark the limits of the resection. The correlation with the subcortical mapping of the anatomic arrangement of the fasciculi with respect to the lesions was complete. The best treatment for brain tumors is maximum resection without associated deficits, so high quality functional studies are necessary for preoperative planning. Copyright © 2011 SERAM. Published by Elsevier Espana. All rights reserved.

4D MRI of polycystic kidneys from rapamycin-treated Glis3-deficient mice

PubMed Central

Xie, Luke; Qi, Yi; Subashi, Ergys; Liao, Grace; Miller DeGraff, Laura; Jetten, Anton M.; Johnson, G. Allan

2015-01-01

Polycystic kidney disease (PKD) is a life-threatening disease that leads to a grotesque enlargement of the kidney and significant lose of function. Several imaging studies with MRI have demonstrated that cyst size in polycystic kidneys can determine disease severity and progression. In the present study, we found that while kidney volume and cyst volume decreased with drug treatment, renal function did not improve with treatment. Here, we applied dynamic contrast-enhanced MRI to study PKD in a Glis3-deficient mouse model. Cysts from this model have a wide range of sizes and develop at an early age. To capture this crucial stage and assess cysts in detail, we imaged during early development (3 to 17 weeks) and applied high spatiotemporal resolution MRI (125×125×125 cubic microns every 7.7 seconds). A drug treatment with rapamycin (also known as sirolimus) was applied to determine whether disease progression could be halted. The effect and synergy (interaction) of aging and treatment were evaluated using an analysis of variance (ANOVA). Structural measurements including kidney volume, cyst volume, and cyst-kidney volume ratio changed significantly with age. Drug treatment significantly decreased these metrics. Functional measurements of time-to-peak (TTP) mean and TTP variance were determined. TTP mean did not change with age, while TTP variance increased with age. The treatment of rapamycin generally did not affect these functional metrics. Synergistic effects of treatment and age were not found for any measurements. Together, the size and volume ratio of cysts decreased with drug treatment, while renal function remained the same. Quantifying renal structure and function with MRI can comprehensively assess the pathophysiology of PKD and response to treatment. PMID:25810360

Longitudinal assessment of childhood optic gliomas: relationship between flicker visual evoked potentials and magnetic resonance imaging findings.

PubMed

Falsini, Benedetto; Ziccardi, Lucia; Lazzareschi, Ilaria; Ruggiero, Antonio; Placentino, Luca; Dickmann, Anna; Liotti, Lucia; Piccardi, Marco; Balestrazzi, Emilio; Colosimo, Cesare; Di Rocco, Concezio; Riccardi, Riccardo

2008-05-01

The aim of this study was to evaluate longitudinally functional and neuro-radiologic findings in childhood optic gliomas (OG), by comparing flicker visual evoked potentials (F-VEPs) with brain magnetic resonance imaging (MRI) changes. Fourteen children (age range: 1-13 years) with OGs underwent serial F-VEP, MRI and neuro-ophthalmic examinations over a 38 month (median, range: 6-76) follow-up. F-VEPs were elicited by 8 Hz sine-wave flicker stimuli presented in a mini-Ganzfeld. Contrast-enhanced MRI examinations were performed. Results of both tests were blindly assessed by independent evaluators. F-VEPs were judged to be improved, stable or worsened if changes in the amplitude and/or phase angle of the response exceeded the limits of test-retest variability (+/-90th percentile) established for the same patients. MRI results were judged to show regression, stabilization or progression of OG based on its changes in size (+/-20%) or extension. Two to seven pairs of F-VEP/MRI examinations per patient (median: 4) were collected. Based on a total of 38 pairs of F-VEP/MRI examinations, both tests agreed in showing worsening (progression), stabilization and improvement (regression) in 5, 15 and 10 cases, respectively. In 3 cases, F-VEPs showed a worsening and MRI a stabilization, while in 5 cases F-VEPs showed an improvement and MRI a stabilization. Agreement between F-VEP and MRI changes was 78.9% (95% CI: +/- 37%, K statistics = 0.67, P < 0.001). The results indicate that longitudinal F-VEP changes can predict changes in MRI-assessed OG size and extension, providing a non-invasive functional assay, complementary to neuro-imaging, for OG follow-up.

The Whole-Brain “Global” Signal from Resting State fMRI as a Potential Biomarker of Quantitative State Changes in Glucose Metabolism

PubMed Central

Thompson, Garth J.; Grimmer, Timo; Drzezga, Alexander; Herman, Peter

2016-01-01

Abstract The evolution of functional magnetic resonance imaging to resting state (R-fMRI) allows measurement of changes in brain networks attributed to state changes, such as in neuropsychiatric diseases versus healthy controls. Since these networks are observed by comparing normalized R-fMRI signals, it is difficult to determine the metabolic basis of such group differences. To investigate the metabolic basis of R-fMRI network differences within a normal range, eyes open versus eyes closed in healthy human subjects was used. R-fMRI was recorded simultaneously with fluoro-deoxyglucose positron emission tomography (FDG-PET). Higher baseline FDG was observed in the eyes open state. Variance-based metrics calculated from R-fMRI did not match the baseline shift in FDG. Functional connectivity density (FCD)-based metrics showed a shift similar to the baseline shift of FDG, however, this was lost if R-fMRI “nuisance signals” were regressed before FCD calculation. Average correlation with the mean R-fMRI signal across the whole brain, generally regarded as a “nuisance signal,” also showed a shift similar to the baseline of FDG. Thus, despite lacking a baseline itself, changes in whole-brain correlation may reflect changes in baseline brain metabolism. Conversely, variance-based metrics may remain similar between states due to inherent region-to-region differences overwhelming the differences between normal physiological states. As most previous studies have excluded the spatial means of R-fMRI metrics from their analysis, this work presents the first evidence of a potential R-fMRI biomarker for baseline shifts in quantifiable metabolism between brain states. PMID:27029438

The Whole-Brain "Global" Signal from Resting State fMRI as a Potential Biomarker of Quantitative State Changes in Glucose Metabolism.

PubMed

Thompson, Garth J; Riedl, Valentin; Grimmer, Timo; Drzezga, Alexander; Herman, Peter; Hyder, Fahmeed

2016-07-01

The evolution of functional magnetic resonance imaging to resting state (R-fMRI) allows measurement of changes in brain networks attributed to state changes, such as in neuropsychiatric diseases versus healthy controls. Since these networks are observed by comparing normalized R-fMRI signals, it is difficult to determine the metabolic basis of such group differences. To investigate the metabolic basis of R-fMRI network differences within a normal range, eyes open versus eyes closed in healthy human subjects was used. R-fMRI was recorded simultaneously with fluoro-deoxyglucose positron emission tomography (FDG-PET). Higher baseline FDG was observed in the eyes open state. Variance-based metrics calculated from R-fMRI did not match the baseline shift in FDG. Functional connectivity density (FCD)-based metrics showed a shift similar to the baseline shift of FDG, however, this was lost if R-fMRI "nuisance signals" were regressed before FCD calculation. Average correlation with the mean R-fMRI signal across the whole brain, generally regarded as a "nuisance signal," also showed a shift similar to the baseline of FDG. Thus, despite lacking a baseline itself, changes in whole-brain correlation may reflect changes in baseline brain metabolism. Conversely, variance-based metrics may remain similar between states due to inherent region-to-region differences overwhelming the differences between normal physiological states. As most previous studies have excluded the spatial means of R-fMRI metrics from their analysis, this work presents the first evidence of a potential R-fMRI biomarker for baseline shifts in quantifiable metabolism between brain states.

Structural and Functional Magnetic Resonance Imaging of the Cerebellum: Considerations for Assessing Cerebellar Ataxias.

PubMed

Deistung, Andreas; Stefanescu, Maria R; Ernst, Thomas M; Schlamann, Marc; Ladd, Mark E; Reichenbach, Jürgen R; Timmann, Dagmar

2016-02-01

Magnetic resonance imaging (MRI) of the brain is of high interest for diagnosing and understanding degenerative ataxias. Here, we present state-of-the-art MRI methods to characterize structural alterations of the cerebellum and introduce initial experiments to show abnormalities in the cerebellar nuclei. Clinically, T1-weighted MR images are used to assess atrophy of the cerebellar cortex, the brainstem, and the spinal cord, whereas T2-weighted and PD-weighted images are typically employed to depict potential white matter lesions that may be associated with certain types of ataxias. More recently, attention has also focused on the characterization of the cerebellar nuclei, which are discernible on spatially highly resolved iron-sensitive MR images due to their relatively high iron content, including T2 (*)-weighted images, susceptibility-weighted images (SWI), effective transverse relaxation rate (R2 (*)) maps, and quantitative susceptibility maps (QSM). Among these iron-sensitive techniques, QSM reveals the best contrast between cerebellar nuclei and their surroundings. In particular, the gyrification of the dentate nuclei is prominently depicted, even at the clinically widely available field strength of 3 T. The linear relationship between magnetic susceptibility and local iron content allows for determination of iron deposition in cerebellar nuclei non-invasively. The increased signal-to-noise ratio of ultrahigh-field MRI (B0 ≥ 7 T) and advances in spatial normalization methods enable functional MRI (fMRI) at the level of the cerebellar cortex and cerebellar nuclei. Data from initial fMRI studies are presented in three common forms of hereditary ataxias (Friedreich's ataxia, spinocerebellar ataxia type 3, and spinocerebellar ataxia type 6). Characteristic changes in the fMRI signal are discussed in the light of histopathological data and current knowledge of the underlying physiology of the fMRI signal in the cerebellum.

“Awake” intraoperative functional MRI (ai-fMRI) for mapping the eloquent cortex: Is it possible in awake craniotomy?☆

PubMed Central

Lu, Jun-Feng; Zhang, Han; Wu, Jin-Song; Yao, Cheng-Jun; Zhuang, Dong-Xiao; Qiu, Tian-Ming; Jia, Wen-Bin; Mao, Ying; Zhou, Liang-Fu

2012-01-01

As a promising noninvasive imaging technique, functional MRI (fMRI) has been extensively adopted as a functional localization procedure for surgical planning. However, the information provided by preoperative fMRI (pre-fMRI) is hampered by the brain deformation that is secondary to surgical procedures. Therefore, intraoperative fMRI (i-fMRI) becomes a potential alternative that can compensate for brain shifts by updating the functional localization information during craniotomy. However, previous i-fMRI studies required that patients be under general anesthesia, preventing the wider application of such a technique as the patients cannot perform tasks unless they are awake. In this study, we propose a new technique that combines awake surgery and i-fMRI, named “awake” i-fMRI (ai-fMRI). We introduced ai-fMRI to the real-time localization of sensorimotor areas during awake craniotomy in seven patients. The results showed that ai-fMRI could successfully detect activations in the bilateral primary sensorimotor areas and supplementary motor areas for all patients, indicating the feasibility of this technique in eloquent area localization. The reliability of ai-fMRI was further validated using intraoperative stimulation mapping (ISM) in two of the seven patients. Comparisons between the pre-fMRI-derived localization result and the ai-fMRI derived result showed that the former was subject to a heavy brain shift and led to incorrect localization, while the latter solved that problem. Additionally, the approaches for the acquisition and processing of the ai-fMRI data were fully illustrated and described. Some practical issues on employing ai-fMRI in awake craniotomy were systemically discussed, and guidelines were provided. PMID:24179766

Resting-state functional connectivity and motor imagery brain activation

PubMed Central

Saiote, Catarina; Tacchino, Andrea; Brichetto, Giampaolo; Roccatagliata, Luca; Bommarito, Giulia; Cordano, Christian; Battaglia, Mario; Mancardi, Giovanni Luigi; Inglese, Matilde

2016-01-01

Motor imagery (MI) relies on the mental simulation of an action without any overt motor execution (ME), and can facilitate motor learning and enhance the effect of rehabilitation in patients with neurological conditions. While functional magnetic resonance imaging (fMRI) during MI and ME reveals shared cortical representations, the role and functional relevance of the resting-state functional connectivity (RSFC) of brain regions involved in MI is yet unknown. Here, we performed resting-state fMRI followed by fMRI during ME and MI with the dominant hand. We used a behavioral chronometry test to measure ME and MI movement duration and compute an index of performance (IP). Then, we analyzed the voxel-matched correlation between the individual MI parameter estimates and seed-based RSFC maps in the MI network to measure the correspondence between RSFC and MI fMRI activation. We found that inter-individual differences in intrinsic connectivity in the MI network predicted several clusters of activation. Taken together, present findings provide first evidence that RSFC within the MI network is predictive of the activation of MI brain regions, including those associated with behavioral performance, thus suggesting a role for RSFC in obtaining a deeper understanding of neural substrates of MI and of MI ability. PMID:27273577

The Use of Functional MRI to Study Appetite Control in the CNS

PubMed Central

De Silva, Akila; Salem, Victoria; Matthews, Paul M.; Dhillo, Waljit S.

2012-01-01

Functional magnetic resonance imaging (fMRI) has provided the opportunity to safely investigate the workings of the human brain. This paper focuses on its use in the field of human appetitive behaviour and its impact in obesity research. In the present absence of any safe or effective centrally acting appetite suppressants, a better understanding of how appetite is controlled is vital for the development of new antiobesity pharmacotherapies. Early functional imaging techniques revealed an attenuation of brain reward area activity in response to visual food stimuli when humans are fed—in other words, the physiological state of hunger somehow increases the appeal value of food. Later studies have investigated the action of appetite modulating hormones on the fMRI signal, showing how the attenuation of brain reward region activity that follows feeding can be recreated in the fasted state by the administration of anorectic gut hormones. Furthermore, differences in brain activity between obese and lean individuals have provided clues about the possible aetiology of overeating. The hypothalamus acts as a central gateway modulating homeostatic and nonhomeostatic drives to eat. As fMRI techniques constantly improve, functional data regarding the role of this small but hugely important structure in appetite control is emerging. PMID:22719753

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

Negative mood influences default mode network functional connectivity in chronic low back pain patients: Implications for functional neuroimaging biomarkers

PubMed Central

Letzen, Janelle E.; Robinson, Michael E.

2016-01-01

The default mode network (DMN) has been proposed as a biomarker for several chronic pain conditions. DMN functional connectivity (fcMRI) is typically examined during resting-state fMRI, in which participants are instructed to let thoughts wander. However, factors at the time of data collection (e.g., negative mood) that might systematically impact pain perception and its brain activity, influencing the application of the DMN as a pain biomarker, are rarely reported. The present study measured whether positive and negative moods altered DMN fcMRI patterns in chronic low back pain (CLBP) patients, specifically focusing on negative mood due to its clinical-relevance. Thirty-three participants (CLBP = 17) underwent resting-state fMRI scanning before and after sad and happy mood inductions, and rated levels of mood and pain intensity at the time of scanning. Two-way repeated measures ANOVAs were conducted on resting-state functional connectivity data. Significant group (CLBP > HC) X condition (sadness > baseline) interaction effects were identified in clusters spanning parietal operculum/postcentral gyrus, insular cortices, anterior cingulate cortex, frontal pole, and a portion of the cerebellum (pFDR < .05). However, only one significant cluster covering a portion of the cerebellum was identified examining a two-way repeated measures ANOVA for happiness > baseline (pFDR < .05). Overall, these findings suggest that DMN fcMRI is affected by negative mood in individuals with and without CLBP. It is possible that DMN fcMRI seen in chronic pain patients is related to an affective dimension of pain, which is important to consider in future neuroimaging biomarker development and implementation. PMID:27583568

A theoretical framework for determining cerebral vascular function and heterogeneity from dynamic susceptibility contrast MRI.

PubMed

Digernes, Ingrid; Bjørnerud, Atle; Vatnehol, Svein Are S; Løvland, Grete; Courivaud, Frédéric; Vik-Mo, Einar; Meling, Torstein R; Emblem, Kyrre E

2017-06-01

Mapping the complex heterogeneity of vascular tissue in the brain is important for understanding cerebrovascular disease. In this translational study, we build on previous work using vessel architectural imaging (VAI) and present a theoretical framework for determining cerebral vascular function and heterogeneity from dynamic susceptibility contrast magnetic resonance imaging (MRI). Our tissue model covers realistic structural architectures for vessel branching and orientations, as well as a range of hemodynamic scenarios for blood flow, capillary transit times and oxygenation. In a typical image voxel, our findings show that the apparent MRI relaxation rates are independent of the mean vessel orientation and that the vortex area, a VAI-based parameter, is determined by the relative oxygen saturation level and the vessel branching of the tissue. Finally, in both simulated and patient data, we show that the relative distributions of the vortex area parameter as a function of capillary transit times show unique characteristics in normal-appearing white and gray matter tissue, whereas tumour-voxels in comparison display a heterogeneous distribution. Collectively, our study presents a comprehensive framework that may serve as a roadmap for in vivo and per-voxel determination of vascular status and heterogeneity in cerebral tissue.

Complementary aspects of diffusion imaging and fMRI; I: structure and function.

PubMed

Mulkern, Robert V; Davis, Peter E; Haker, Steven J; Estepar, Raul San Jose; Panych, Lawrence P; Maier, Stephan E; Rivkin, Michael J

2006-05-01

Studying the intersection of brain structure and function is an important aspect of modern neuroscience. The development of magnetic resonance imaging (MRI) over the last 25 years has provided new and powerful tools for the study of brain structure and function. Two tools in particular, diffusion imaging and functional MRI (fMRI), are playing increasingly important roles in elucidating the complementary aspects of brain structure and function. In this work, we review basic technical features of diffusion imaging and fMRI for studying the integrity of white matter structural components and for determining the location and extent of cortical activation in gray matter, respectively. We then review a growing body of literature in which the complementary aspects of diffusion imaging and fMRI, applied as separate examinations but analyzed in tandem, have been exploited to enhance our knowledge of brain structure and function.

MRI-based dynamic tracking of an untethered ferromagnetic microcapsule navigating in liquid

NASA Astrophysics Data System (ADS)

Dahmen, Christian; Belharet, Karim; Folio, David; Ferreira, Antoine; Fatikow, Sergej

2016-04-01

The propulsion of ferromagnetic objects by means of MRI gradients is a promising approach to enable new forms of therapy. In this work, necessary techniques are presented to make this approach work. This includes path planning algorithms working on MRI data, ferromagnetic artifact imaging and a tracking algorithm which delivers position feedback for the ferromagnetic objects, and a propulsion sequence to enable interleaved magnetic propulsion and imaging. Using a dedicated software environment, integrating path-planning methods and real-time tracking, a clinical MRI system is adapted to provide this new functionality for controlled interventional targeted therapeutic applications. Through MRI-based sensing analysis, this article aims to propose a framework to plan a robust pathway to enhance the navigation ability to reach deep locations in the human body. The proposed approaches are validated with different experiments.

Comparison of causality analysis on simultaneously measured fMRI and NIRS signals during motor tasks.

PubMed

Anwar, Abdul Rauf; Muthalib, Makii; Perrey, Stephane; Galka, Andreas; Granert, Oliver; Wolff, Stephan; Deuschl, Guenther; Raethjen, Jan; Heute, Ulrich; Muthuraman, Muthuraman

2013-01-01

Brain activity can be measured using different modalities. Since most of the modalities tend to complement each other, it seems promising to measure them simultaneously. In to be presented research, the data recorded from Functional Magnetic Resonance Imaging (fMRI) and Near Infrared Spectroscopy (NIRS), simultaneously, are subjected to causality analysis using time-resolved partial directed coherence (tPDC). Time-resolved partial directed coherence uses the principle of state space modelling to estimate Multivariate Autoregressive (MVAR) coefficients. This method is useful to visualize both frequency and time dynamics of causality between the time series. Afterwards, causality results from different modalities are compared by estimating the Spearman correlation. In to be presented study, we used directionality vectors to analyze correlation, rather than actual signal vectors. Results show that causality analysis of the fMRI correlates more closely to causality results of oxy-NIRS as compared to deoxy-NIRS in case of a finger sequencing task. However, in case of simple finger tapping, no clear difference between oxy-fMRI and deoxy-fMRI correlation is identified.

Implementation of time-efficient adaptive sampling function design for improved undersampled MRI reconstruction

NASA Astrophysics Data System (ADS)

Choi, Jinhyeok; Kim, Hyeonjin

2016-12-01

To improve the efficacy of undersampled MRI, a method of designing adaptive sampling functions is proposed that is simple to implement on an MR scanner and yet effectively improves the performance of the sampling functions. An approximation of the energy distribution of an image (E-map) is estimated from highly undersampled k-space data acquired in a prescan and efficiently recycled in the main scan. An adaptive probability density function (PDF) is generated by combining the E-map with a modeled PDF. A set of candidate sampling functions are then prepared from the adaptive PDF, among which the one with maximum energy is selected as the final sampling function. To validate its computational efficiency, the proposed method was implemented on an MR scanner, and its robust performance in Fourier-transform (FT) MRI and compressed sensing (CS) MRI was tested by simulations and in a cherry tomato. The proposed method consistently outperforms the conventional modeled PDF approach for undersampling ratios of 0.2 or higher in both FT-MRI and CS-MRI. To fully benefit from undersampled MRI, it is preferable that the design of adaptive sampling functions be performed online immediately before the main scan. In this way, the proposed method may further improve the efficacy of the undersampled MRI.

Reduced fMRI activity predicts relapse in patients recovering from stimulant dependence.

PubMed

Clark, Vincent P; Beatty, Gregory K; Anderson, Robert E; Kodituwakku, Piyadassa; Phillips, John P; Lane, Terran D R; Kiehl, Kent A; Calhoun, Vince D

2014-02-01

Relapse presents a significant problem for patients recovering from stimulant dependence. Here we examined the hypothesis that patterns of brain function obtained at an early stage of abstinence differentiates patients who later relapse versus those who remain abstinent. Forty-five recently abstinent stimulant-dependent patients were tested using a randomized event-related functional MRI (ER-fMRI) design that was developed in order to replicate a previous ERP study of relapse using a selective attention task, and were then monitored until 6 months of verified abstinence or stimulant use occurred. SPM revealed smaller absolute blood oxygen level-dependent (BOLD) response amplitude in bilateral ventral posterior cingulate and right insular cortex in 23 patients positive for relapse to stimulant use compared with 22 who remained abstinent. ER-fMRI, psychiatric, neuropsychological, demographic, personal and family history of drug use were compared in order to form predictive models. ER-fMRI was found to predict abstinence with higher accuracy than any other single measure obtained in this study. Logistic regression using fMRI amplitude in right posterior cingulate and insular cortex predicted abstinence with 77.8% accuracy, which increased to 89.9% accuracy when history of mania was included. Using 10-fold cross-validation, Bayesian logistic regression and multilayer perceptron algorithms provided the highest accuracy of 84.4%. These results, combined with previous studies, suggest that the functional organization of paralimbic brain regions including ventral anterior and posterior cingulate and right insula are related to patients' ability to maintain abstinence. Novel therapies designed to target these paralimbic regions identified using ER-fMRI may improve treatment outcome. Copyright © 2012 Wiley Periodicals, Inc.

A longitudinal model for functional connectivity networks using resting-state fMRI.

PubMed

Hart, Brian; Cribben, Ivor; Fiecas, Mark

2018-06-04

Many neuroimaging studies collect functional magnetic resonance imaging (fMRI) data in a longitudinal manner. However, the current fMRI literature lacks a general framework for analyzing functional connectivity (FC) networks in fMRI data obtained from a longitudinal study. In this work, we build a novel longitudinal FC model using a variance components approach. First, for all subjects' visits, we account for the autocorrelation inherent in the fMRI time series data using a non-parametric technique. Second, we use a generalized least squares approach to estimate 1) the within-subject variance component shared across the population, 2) the baseline FC strength, and 3) the FC's longitudinal trend. Our novel method for longitudinal FC networks seeks to account for the within-subject dependence across multiple visits, the variability due to the subjects being sampled from a population, and the autocorrelation present in fMRI time series data, while restricting the number of parameters in order to make the method computationally feasible and stable. We develop a permutation testing procedure to draw valid inference on group differences in the baseline FC network and change in FC over longitudinal time between a set of patients and a comparable set of controls. To examine performance, we run a series of simulations and apply the model to longitudinal fMRI data collected from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Overall, we found no difference in the global FC network between Alzheimer's disease patients and healthy controls, but did find differing local aging patterns in the FC between the left hippocampus and the posterior cingulate cortex. Copyright © 2018 Elsevier Inc. All rights reserved.

fMRI neurofeedback of amygdala response to aversive stimuli enhances prefrontal-limbic brain connectivity.

PubMed

Paret, Christian; Ruf, Matthias; Gerchen, Martin Fungisai; Kluetsch, Rosemarie; Demirakca, Traute; Jungkunz, Martin; Bertsch, Katja; Schmahl, Christian; Ende, Gabriele

2016-01-15

Down-regulation of the amygdala with real-time fMRI neurofeedback (rtfMRI NF) potentially allows targeting brain circuits of emotion processing and may involve prefrontal-limbic networks underlying effective emotion regulation. Little research has been dedicated to the effect of rtfMRI NF on the functional connectivity of the amygdala and connectivity patterns in amygdala down-regulation with neurofeedback have not been addressed yet. Using psychophysiological interaction analysis of fMRI data, we present evidence that voluntary amygdala down-regulation by rtfMRI NF while viewing aversive pictures was associated with increased connectivity of the right amygdala with the ventromedial prefrontal cortex (vmPFC) in healthy subjects (N=16). In contrast, a control group (N=16) receiving sham feedback did not alter amygdala connectivity (Group×Condition t-contrast: p<.05 at cluster-level). Task-dependent increases in amygdala-vmPFC connectivity were predicted by picture arousal (β=.59, p<.05). A dynamic causal modeling analysis with Bayesian model selection aimed at further characterizing the underlying causal structure and favored a bottom-up model assuming predominant information flow from the amygdala to the vmPFC (xp=.90). The results were complemented by the observation of task-dependent alterations in functional connectivity of the vmPFC with the visual cortex and the ventrolateral PFC in the experimental group (Condition t-contrast: p<.05 at cluster-level). Taken together, the results underscore the potential of amygdala fMRI neurofeedback to influence functional connectivity in key networks of emotion processing and regulation. This may be beneficial for patients suffering from severe emotion dysregulation by improving neural self-regulation. Copyright © 2015 Elsevier Inc. All rights reserved.

Event-related functional MRI: Past, present, and future

PubMed Central

Rosen, Bruce R.; Buckner, Randy L.; Dale, Anders M.

1998-01-01

The past two decades have seen an enormous growth in the field of human brain mapping. Investigators have extensively exploited techniques such as positron emission tomography and MRI to map patterns of brain activity based on changes in cerebral hemodynamics. However, until recently, most studies have investigated equilibrium changes in blood flow measured over time periods upward of 1 min. The advent of high-speed MRI methods, capable of imaging the entire brain with a temporal resolution of a few seconds, allows for brain mapping based on more transient aspects of the hemodynamic response. Today it is now possible to map changes in cerebrovascular parameters essentially in real time, conferring the ability to observe changes in brain state that occur over time periods of seconds. Furthermore, because robust hemodynamic alterations are detectable after neuronal stimuli lasting only a few tens of milliseconds, a new class of task paradigms designed to measure regional responses to single sensory or cognitive events can now be studied. Such “event related” functional MRI should provide for fundamentally new ways to interrogate brain function, and allow for the direct comparison and ultimately integration of data acquired by using more traditional behavioral and electrophysiological methods. PMID:9448240

Enhanced Thalamic Functional Connectivity with No fMRI Responses to Affected Forelimb Stimulation in Stroke-Recovered Rats.

PubMed

Shim, Woo H; Suh, Ji-Yeon; Kim, Jeong K; Jeong, Jaeseung; Kim, Young R

2016-01-01

Neurological recovery after stroke has been extensively investigated to provide better understanding of neurobiological mechanism, therapy, and patient management. Recent advances in neuroimaging techniques, particularly functional MRI (fMRI), have widely contributed to unravel the relationship between the altered neural function and stroke-affected brain areas. As results of previous investigations, the plastic reorganization and/or gradual restoration of the hemodynamic fMRI responses to neural stimuli have been suggested as relevant mechanisms underlying the stroke recovery process. However, divergent study results and modality-dependent outcomes have clouded the proper interpretation of variable fMRI signals. Here, we performed both evoked and resting state fMRI (rs-fMRI) to clarify the link between the fMRI phenotypes and post-stroke functional recovery. The experiments were designed to examine the altered neural activity within the contra-lesional hemisphere and other undamaged brain regions using rat models with large unilateral stroke, which despite the severe injury, exhibited nearly full recovery at ∼6 months after stroke. Surprisingly, both blood oxygenation level-dependent and blood volume-weighted (CBVw) fMRI activities elicited by electrical stimulation of the stroke-affected forelimb were completely absent, failing to reveal the neural origin of the behavioral recovery. In contrast, the functional connectivity maps showed highly robust rs-fMRI activity concentrated in the contra-lesional ventromedial nucleus of thalamus (VM). The negative finding in the stimuli-induced fMRI study using the popular rat middle cerebral artery model denotes weak association between the fMRI hemodynamic responses and neurological improvement. The results strongly caution the indiscreet interpretation of stroke-affected fMRI signals and demonstrate rs-fMRI as a complementary tool for efficiently characterizing stroke recovery.

Functional overestimation due to spatial smoothing of fMRI data.

PubMed

Liu, Peng; Calhoun, Vince; Chen, Zikuan

2017-11-01

Pearson correlation (simply correlation) is a basic technique for neuroimage function analysis. It has been observed that the spatial smoothing may cause functional overestimation, which however remains a lack of complete understanding. Herein, we present a theoretical explanation from the perspective of correlation scale invariance. For a task-evoked spatiotemporal functional dataset, we can extract the functional spatial map by calculating the temporal correlations (tcorr) of voxel timecourses against the task timecourse. From the relationship between image noise level (changed through spatial smoothing) and the tcorr map calculation, we show that the spatial smoothing causes a noise reduction, which in turn smooths the tcorr map and leads to a spatial expansion on neuroactivity blob estimation. Through numerical simulations and subject experiments, we show that the spatial smoothing of fMRI data may overestimate activation spots in the correlation functional map. Our results suggest a small spatial smoothing (with a smoothing kernel with a full width at half maximum (FWHM) of no more than two voxels) on fMRI data processing for correlation-based functional mapping COMPARISON WITH EXISTING METHODS: In extreme noiselessness, the correlation of scale-invariance property defines a meaningless binary tcorr map. In reality, a functional activity blob in a tcorr map is shaped due to the spoilage of image noise on correlative responses. We may reduce data noise level by smoothing processing, which poses a smoothing effect on correlation. This logic allows us to understand the noise dependence and the smoothing effect of correlation-based fMRI data analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

Magnetic Resonance Imaging and Functional Outcomes After a Polyurethane Meniscal Scaffold Implantation: Minimum 5-Year Follow-up.

PubMed

Monllau, Joan C; Poggioli, Francesco; Erquicia, Juan; Ramírez, Eduardo; Pelfort, Xavier; Gelber, Pablo; Torres-Claramunt, Raúl

2018-05-01

To report the magnetic resonance imaging (MRI) and clinical outcomes at a minimum 5-year follow-up in a series of patients with postmeniscectomy syndrome and treated with a polyurethane scaffold. All consecutive patients operated on from September 2008 to February 2011 for either persistent medial or lateral joint line compartmental pain receiving a polyurethane scaffold due to a previous partial meniscus resection with a minimum 5-year follow-up were included. Functional scores (Knee Injury and Osteoarthritis Outcomes Score, International Knee Documentation Committee, Lysholm, and Tegner) were assessed preoperatively and at the last follow-up. The state of the scaffold as well as postoperative scaffold extrusion and the total remaining meniscal volume was also evaluated in MRI. Thirty-two patients were included. The mean follow-up was 70.8 ± 7.5 months. The functionality of the knees improved in all the scores used (P < .001) except for the Tegner score that stayed steady. Most of meniscal implants showed extrusion of 2.4 mm (95% confidence interval [CI], 1.1-3.7) were smaller and a hyperintensity signal was seen in the MRI. Three scaffolds were resorbed at the last follow-up. The meniscal volume, determined by MRI, was 1.14 cm 3 (95% CI, 0.96-1.31) preoperatively and 1.61 cm 3 (95% CI, 1.43-1.7) at the last follow-up. No differences were presented. The use of a polyurethane meniscal scaffold in patients with a symptomatic meniscus deficit had a good functional outcome at 5 years after surgery. However, the implanted scaffolds did not present normal meniscal tissue with MRI, and the implant volume was considerably less than expected. The fact that most of patients included received different concomitant procedures during scaffold implantation introduces a degree of performance bias into the results. Level IV, case series. Copyright © 2018 Arthroscopy Association of North America. Published by Elsevier Inc. All rights reserved.

Validity of semi-quantitative scale for brain MRI in unilateral cerebral palsy due to periventricular white matter lesions: Relationship with hand sensorimotor function and structural connectivity.

PubMed

Fiori, Simona; Guzzetta, Andrea; Pannek, Kerstin; Ware, Robert S; Rossi, Giuseppe; Klingels, Katrijn; Feys, Hilde; Coulthard, Alan; Cioni, Giovanni; Rose, Stephen; Boyd, Roslyn N

2015-01-01

To provide first evidence of construct validity of a semi-quantitative scale for brain structural MRI (sqMRI scale) in children with unilateral cerebral palsy (UCP) secondary to periventricular white matter (PWM) lesions, by examining the relationship with hand sensorimotor function and whole brain structural connectivity. Cross-sectional study of 50 children with UCP due to PWM lesions using 3 T (MRI), diffusion MRI and assessment of hand sensorimotor function. We explored the relationship of lobar, hemispheric and global scores on the sqMRI scale, with fractional anisotropy (FA), as a measure of brain white matter microstructure, and with hand sensorimotor measures (Assisting Hand Assessment, AHA; Jebsen-Taylor Test for Hand Function, JTTHF; Melbourne Assessment of Unilateral Upper Limb Function, MUUL; stereognosis; 2-point discrimination). Lobar and hemispheric scores on the sqMRI scale contralateral to the clinical side of hemiplegia correlated with sensorimotor paretic hand function measures and FA of a number of brain structural connections, including connections of brain areas involved in motor control (postcentral, precentral and paracentral gyri in the parietal lobe). More severe lesions correlated with lower sensorimotor performance, with the posterior limb of internal capsule score being the strongest contributor to impaired hand function. The sqMRI scale demonstrates first evidence of construct validity against impaired motor and sensory function measures and brain structural connectivity in a cohort of children with UCP due to PWM lesions. More severe lesions correlated with poorer paretic hand sensorimotor function and impaired structural connectivity in the hemisphere contralateral to the clinical side of hemiplegia. The quantitative structural MRI scoring may be a useful clinical tool for studying brain structure-function relationships but requires further validation in other populations of CP.

The effect of ageing on fMRI: Correction for the confounding effects of vascular reactivity evaluated by joint fMRI and MEG in 335 adults.

PubMed

Tsvetanov, Kamen A; Henson, Richard N A; Tyler, Lorraine K; Davis, Simon W; Shafto, Meredith A; Taylor, Jason R; Williams, Nitin; Cam-Can; Rowe, James B

2015-06-01

In functional magnetic resonance imaging (fMRI) research one is typically interested in neural activity. However, the blood-oxygenation level-dependent (BOLD) signal is a composite of both neural and vascular activity. As factors such as age or medication may alter vascular function, it is essential to account for changes in neurovascular coupling when investigating neurocognitive functioning with fMRI. The resting-state fluctuation amplitude (RSFA) in the fMRI signal (rsfMRI) has been proposed as an index of vascular reactivity. The RSFA compares favourably with other techniques such as breath-hold and hypercapnia, but the latter are more difficult to perform in some populations, such as older adults. The RSFA is therefore a candidate for use in adjusting for age-related changes in vascular reactivity in fMRI studies. The use of RSFA is predicated on its sensitivity to vascular rather than neural factors; however, the extent to which each of these factors contributes to RSFA remains to be characterized. The present work addressed these issues by comparing RSFA (i.e., rsfMRI variability) to proxy measures of (i) cardiovascular function in terms of heart rate (HR) and heart rate variability (HRV) and (ii) neural activity in terms of resting state magnetoencephalography (rsMEG). We derived summary scores of RSFA, a sensorimotor task BOLD activation, cardiovascular function and rsMEG variability for 335 healthy older adults in the population-based Cambridge Centre for Ageing and Neuroscience cohort (Cam-CAN; www.cam-can.com). Mediation analysis revealed that the effects of ageing on RSFA were significantly mediated by vascular factors, but importantly not by the variability in neuronal activity. Furthermore, the converse effects of ageing on the rsMEG variability were not mediated by vascular factors. We then examined the effect of RSFA scaling of task-based BOLD in the sensorimotor task. The scaling analysis revealed that much of the effects of age on task-based activation studies with fMRI do not survive correction for changes in vascular reactivity, and are likely to have been overestimated in previous fMRI studies of ageing. The results from the mediation analysis demonstrate that RSFA is modulated by measures of vascular function and is not driven solely by changes in the variance of neural activity. Based on these findings we propose that the RSFA scaling method is articularly useful in large scale and longitudinal neuroimaging studies of ageing, or with frail participants, where alternative measures of vascular reactivity are impractical. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

The effect of ageing on fMRI: Correction for the confounding effects of vascular reactivity evaluated by joint fMRI and MEG in 335 adults

PubMed Central

Henson, Richard N. A.; Tyler, Lorraine K.; Davis, Simon W.; Shafto, Meredith A.; Taylor, Jason R.; Williams, Nitin; Cam‐CAN; Rowe, James B.

2015-01-01

Abstract In functional magnetic resonance imaging (fMRI) research one is typically interested in neural activity. However, the blood‐oxygenation level‐dependent (BOLD) signal is a composite of both neural and vascular activity. As factors such as age or medication may alter vascular function, it is essential to account for changes in neurovascular coupling when investigating neurocognitive functioning with fMRI. The resting‐state fluctuation amplitude (RSFA) in the fMRI signal (rsfMRI) has been proposed as an index of vascular reactivity. The RSFA compares favourably with other techniques such as breath‐hold and hypercapnia, but the latter are more difficult to perform in some populations, such as older adults. The RSFA is therefore a candidate for use in adjusting for age‐related changes in vascular reactivity in fMRI studies. The use of RSFA is predicated on its sensitivity to vascular rather than neural factors; however, the extent to which each of these factors contributes to RSFA remains to be characterized. The present work addressed these issues by comparing RSFA (i.e., rsfMRI variability) to proxy measures of (i) cardiovascular function in terms of heart rate (HR) and heart rate variability (HRV) and (ii) neural activity in terms of resting state magnetoencephalography (rsMEG). We derived summary scores of RSFA, a sensorimotor task BOLD activation, cardiovascular function and rsMEG variability for 335 healthy older adults in the population‐based Cambridge Centre for Ageing and Neuroscience cohort (Cam‐CAN; www.cam-can.com). Mediation analysis revealed that the effects of ageing on RSFA were significantly mediated by vascular factors, but importantly not by the variability in neuronal activity. Furthermore, the converse effects of ageing on the rsMEG variability were not mediated by vascular factors. We then examined the effect of RSFA scaling of task‐based BOLD in the sensorimotor task. The scaling analysis revealed that much of the effects of age on task‐based activation studies with fMRI do not survive correction for changes in vascular reactivity, and are likely to have been overestimated in previous fMRI studies of ageing. The results from the mediation analysis demonstrate that RSFA is modulated by measures of vascular function and is not driven solely by changes in the variance of neural activity. Based on these findings we propose that the RSFA scaling method is articularly useful in large scale and longitudinal neuroimaging studies of ageing, or with frail participants, where alternative measures of vascular reactivity are impractical. Hum Brain Mapp 36:2248–2269, 2015. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. PMID:25727740

Realistic simulated MRI and SPECT databases. Application to SPECT/MRI registration evaluation.

PubMed

Aubert-Broche, Berengere; Grova, Christophe; Reilhac, Anthonin; Evans, Alan C; Collins, D Louis

2006-01-01

This paper describes the construction of simulated SPECT and MRI databases that account for realistic anatomical and functional variability. The data is used as a gold-standard to evaluate four SPECT/MRI similarity-based registration methods. Simulation realism was accounted for using accurate physical models of data generation and acquisition. MRI and SPECT simulations were generated from three subjects to take into account inter-subject anatomical variability. Functional SPECT data were computed from six functional models of brain perfusion. Previous models of normal perfusion and ictal perfusion observed in Mesial Temporal Lobe Epilepsy (MTLE) were considered to generate functional variability. We studied the impact noise and intensity non-uniformity in MRI simulations and SPECT scatter correction may have on registration accuracy. We quantified the amount of registration error caused by anatomical and functional variability. Registration involving ictal data was less accurate than registration involving normal data. MR intensity nonuniformity was the main factor decreasing registration accuracy. The proposed simulated database is promising to evaluate many functional neuroimaging methods, involving MRI and SPECT data.

Resection and Resolution of Bone Marrow Lesions Associated with an Improvement of Pain after Total Knee Replacement: A Novel Case Study Using a 3-Tesla Metal Artefact Reduction MRI Sequence.

PubMed

Kurien, Thomas; Kerslake, Robert; Haywood, Brett; Pearson, Richard G; Scammell, Brigitte E

2016-01-01

We present our case report using a novel metal artefact reduction magnetic resonance imaging (MRI) sequence to observe resolution of subchondral bone marrow lesions (BMLs), which are strongly associated with pain, in a patient after total knee replacement surgery. Large BMLs were seen preoperatively on the 3-Tesla MRI scans in a patient with severe end stage OA awaiting total knee replacement surgery. Twelve months after surgery, using a novel metal artefact reduction MRI sequence, we were able to visualize the bone-prosthesis interface and found complete resection and resolution of these BMLs. This is the first reported study in the UK to use this metal artefact reduction MRI sequence at 3-Tesla showing that resection and resolution of BMLs in this patient were associated with an improvement of pain and function after total knee replacement surgery. In this case it was associated with a clinically significant improvement of pain and function after surgery. Failure to eradicate these lesions may be a cause of persistent postoperative pain that is seen in up to 20% of patients following TKR surgery.

The inclusion of functional connectivity information into fMRI-based neurofeedback improves its efficacy in the reduction of cigarette cravings.

PubMed

Kim, Dong-Youl; Yoo, Seung-Schik; Tegethoff, Marion; Meinlschmidt, Gunther; Lee, Jong-Hwan

2015-08-01

Real-time fMRI (rtfMRI) neurofeedback (NF) facilitates volitional control over brain activity and the modulation of associated mental functions. The NF signals of traditional rtfMRI-NF studies predominantly reflect neuronal activity within ROIs. In this study, we describe a novel rtfMRI-NF approach that includes a functional connectivity (FC) component in the NF signal (FC-added rtfMRI-NF). We estimated the efficacy of the FC-added rtfMRI-NF method by applying it to nicotine-dependent heavy smokers in an effort to reduce cigarette craving. ACC and medial pFC as well as the posterior cingulate cortex and precuneus are associated with cigarette craving and were chosen as ROIs. Fourteen heavy smokers were randomly assigned to receive one of two types of NF: traditional activity-based rtfMRI-NF or FC-added rtfMRI-NF. Participants received rtfMRI-NF training during two separate visits after overnight smoking cessation, and cigarette craving score was assessed. The FC-added rtfMRI-NF resulted in greater neuronal activity and increased FC between the targeted ROIs than the traditional activity-based rtfMRI-NF and resulted in lower craving score. In the FC-added rtfMRI-NF condition, the average of neuronal activity and FC was tightly associated with craving score (Bonferroni-corrected p = .028). However, in the activity-based rtfMRI-NF condition, no association was detected (uncorrected p > .081). Non-rtfMRI data analysis also showed enhanced neuronal activity and FC with FC-added NF than with activity-based NF. These results demonstrate that FC-added rtfMRI-NF facilitates greater volitional control over brain activity and connectivity and greater modulation of mental function than activity-based rtfMRI-NF.

Hyperactive external awareness against hypoactive internal awareness in disorders of consciousness using resting-state functional MRI: highlighting the involvement of visuo-motor modulation.

PubMed

He, Jiang-Hong; Yang, Yi; Zhang, Yi; Qiu, Si-You; Zhou, Zhen-Yu; Dang, Yuan-Yuan; Dai, Yi-Wu; Liu, Yi-Jun; Xu, Ru-Xiang

2014-08-01

Resting-state functional MRI (fMRI) has emerged as a valuable tool to characterize the complex states encompassing disorders of consciousness (DOC). Awareness appears to comprise two coexistent, anticorrelated components named the external and internal awareness networks. The present study hypothesizes that DOC interrupts the balance between the internal and external awareness networks. To gain more understanding of this phenomenon, the present study analyzed resting-state fMRI data from 12 patients with DOC versus 12 healthy age-matched controls. The data were explored using independent component analysis and amplitude of low-frequency fluctuation (ALFF) analysis. The results indicated that DOC deactivated midline areas associated with internal awareness. In addition, external awareness was strengthened in DOC because of increased activation in the insula, lingual gyrus, paracentral and supplementary motor area. The activity patterns suggested strengthened external awareness against weakened internal awareness in DOC. In particular, increased activity found in the insula, lingual gyrus, paracentral and supplementary motor area of patients with DOC implied possible involvement of augmented visuo-motor modulation in these patients. DOC is probably related to hyperactive external awareness opposing hypoactive internal awareness. This unique pattern of brain activity may potentially be a prognostic marker for DOC. Copyright © 2014 John Wiley & Sons, Ltd.

EEG, PET, SPET and MRI in intractable childhood epilepsies: possible surgical correlations.

PubMed

Fois, A; Farnetani, M A; Balestri, P; Buoni, S; Di Cosmo, G; Vattimo, A; Guazzelli, M; Guzzardi, R; Salvadori, P A

1995-12-01

Magnetic resonance imaging (MRI), single photon emission tomography (SPET), and positron emission tomography (PET) using [18F]fluorodeoxyglucose were used in combination with scalp and scalp-video EEGs in a group of 30 pediatric patients with drug resistant epilepsy (DRE) in order to identify patients who could benefit from neurosurgical approach. Seizures were classified according to the consensus criteria of The International League Against Epilepsy. In three patients infantile spasms (IS) were diagnosed; 13 subjects were affected by different types of generalized seizures, associated with complex partial seizures (CPS) in three. In the other 14 patients partial seizures, either simple (SPS) or complex, were present. A localized abnormality was demonstrated in one patient with IS and in three patients with generalized seizures. Of the group of 14 subjects with CPS, MRI and CT were normal in 7, but SPET or PET indicated focal hypoperfusion or hypometabolism concordant with the localization of the EEG abnormalities. In 5 of the other 7 patients anatomical and functional imaging and EEG findings were concordant for a localized abnormality. It can be concluded that functional imaging combined with scalp EEGs appears to be superior to the use of only CT and MRI for selecting children with epilepsy in whom a surgical approach can be considered, in particular when CPS resistant to therapy are present.

Stimulus-induced dissociation of neuronal firing rates and local field potential gamma power and its relationship to the blood oxygen level-dependent signal in macaque primary visual cortex

PubMed Central

Bartolo, M J; Gieselmann, M A; Vuksanovic, V; Hunter, D; Sun, L; Chen, X; Delicato, L S; Thiele, A

2011-01-01

The functional magnetic resonance imaging (fMRI) blood oxygenation level-dependent (BOLD) signal is regularly used to assign neuronal activity to cognitive function. Recent analyses have shown that the local field potential (LFP) gamma power is a better predictor of the fMRI BOLD signal than spiking activity. However, LFP gamma power and spiking activity are usually correlated, clouding the analysis of the neural basis of the BOLD signal. We show that changes in LFP gamma power and spiking activity in the primary visual cortex (V1) of the awake primate can be dissociated by using grating and plaid pattern stimuli, which differentially engage surround suppression and cross-orientation inhibition/facilitation within and between cortical columns. Grating presentation yielded substantial V1 LFP gamma frequency oscillations and significant multi-unit activity. Plaid pattern presentation significantly reduced the LFP gamma power while increasing population multi-unit activity. The fMRI BOLD activity followed the LFP gamma power changes, not the multi-unit activity. Inference of neuronal activity from the fMRI BOLD signal thus requires detailed a priori knowledge of how different stimuli or tasks activate the cortical network. PMID:22081989

Physiological self-regulation of regional brain activity using real-time functional magnetic resonance imaging (fMRI): methodology and exemplary data.

PubMed

Weiskopf, Nikolaus; Veit, Ralf; Erb, Michael; Mathiak, Klaus; Grodd, Wolfgang; Goebel, Rainer; Birbaumer, Niels

2003-07-01

A brain-computer interface (BCI) based on real-time functional magnetic resonance imaging (fMRI) is presented which allows human subjects to observe and control changes of their own blood oxygen level-dependent (BOLD) response. This BCI performs data preprocessing (including linear trend removal, 3D motion correction) and statistical analysis on-line. Local BOLD signals are continuously fed back to the subject in the magnetic resonance scanner with a delay of less than 2 s from image acquisition. The mean signal of a region of interest is plotted as a time-series superimposed on color-coded stripes which indicate the task, i.e., to increase or decrease the BOLD signal. We exemplify the presented BCI with one volunteer intending to control the signal of the rostral-ventral and dorsal part of the anterior cingulate cortex (ACC). The subject achieved significant changes of local BOLD responses as revealed by region of interest analysis and statistical parametric maps. The percent signal change increased across fMRI-feedback sessions suggesting a learning effect with training. This methodology of fMRI-feedback can assess voluntary control of circumscribed brain areas. As a further extension, behavioral effects of local self-regulation become accessible as a new field of research.

Whole-brain functional magnetic resonance imaging mapping of acute nociceptive responses induced by formalin in rats using atlas registration-based event-related analysis.

PubMed

Shih, Yen-Yu I; Chen, You-Yin; Chen, Chiao-Chi V; Chen, Jyh-Cheng; Chang, Chen; Jaw, Fu-Shan

2008-06-01

Nociceptive neuronal activation in subcortical regions has not been well investigated in functional magnetic resonance imaging (fMRI) studies. The present report aimed to use the blood oxygenation level-dependent (BOLD) fMRI technique to map nociceptive responses in both subcortical and cortical regions by employing a refined data processing method, the atlas registration-based event-related (ARBER) analysis technique. During fMRI acquisition, 5% formalin (50 mul) was injected into the left hindpaw to induce nociception. ARBER was then used to normalize the data among rats, and images were analyzed using automatic selection of the atlas-based region of interest. It was found that formalin-induced nociceptive processing increased BOLD signals in both cortical and subcortical regions. The cortical activation was distributed over the cingulate, motor, somatosensory, insular, and visual cortices, and the subcortical activation involved the caudate putamen, hippocampus, periaqueductal gray, superior colliculus, thalamus, and hypothalamus. With the aid of ARBER, the present study revealed a detailed activation pattern that possibly indicated the recruitment of various parts of the nociceptive system. The results also demonstrated the utilization of ARBER in establishing an fMRI-based whole-brain nociceptive map. The formalin induced nociceptive images may serve as a template of central nociceptive responses, which can facilitate the future use of fMRI in evaluation of new drugs and preclinical therapies for pain. (c) 2008 Wiley-Liss, Inc.

Laminar fMRI and computational theories of brain function.

PubMed

Stephan, K E; Petzschner, F H; Kasper, L; Bayer, J; Wellstein, K V; Stefanics, G; Pruessmann, K P; Heinzle, J

2017-11-02

Recently developed methods for functional MRI at the resolution of cortical layers (laminar fMRI) offer a novel window into neurophysiological mechanisms of cortical activity. Beyond physiology, laminar fMRI also offers an unprecedented opportunity to test influential theories of brain function. Specifically, hierarchical Bayesian theories of brain function, such as predictive coding, assign specific computational roles to different cortical layers. Combined with computational models, laminar fMRI offers a unique opportunity to test these proposals noninvasively in humans. This review provides a brief overview of predictive coding and related hierarchical Bayesian theories, summarises their predictions with regard to layered cortical computations, examines how these predictions could be tested by laminar fMRI, and considers methodological challenges. We conclude by discussing the potential of laminar fMRI for clinically useful computational assays of layer-specific information processing. Copyright © 2017 Elsevier Inc. All rights reserved.

[Rupture of lateral ligaments of the ankle joint: MR imaging before and after functional therapy].

PubMed

Grebe, P; Kreitner, K F; Roeder, W; Kersjes, W; Hennes, R; Runkel, M

1995-09-01

Documentation via MRI of the healing of ruptured lateral collateral ankle ligaments after functional therapy. 35 patients with ankle sprain were examined by MRI and stress radiographs, 13 were operated afterwards, 22 patients underwent a functional conservative therapy and were examined by MRI and stress radiographs and second time after three months. MRI reports were correct in 12 of 13 operated cases. After conservative therapy we did not find any disrupted ankle ligament. MRI showed intact ligaments thickened by scar. MRI is able to show injuries of the lateral collateral ankle ligaments and demonstrates the healing by scar after conservative therapy.

Characterization of the blood-oxygen level-dependent (BOLD) response in cat auditory cortex using high-field fMRI.

PubMed

Brown, Trecia A; Joanisse, Marc F; Gati, Joseph S; Hughes, Sarah M; Nixon, Pam L; Menon, Ravi S; Lomber, Stephen G

2013-01-01

Much of what is known about the cortical organization for audition in humans draws from studies of auditory cortex in the cat. However, these data build largely on electrophysiological recordings that are both highly invasive and provide less evidence concerning macroscopic patterns of brain activation. Optical imaging, using intrinsic signals or dyes, allows visualization of surface-based activity but is also quite invasive. Functional magnetic resonance imaging (fMRI) overcomes these limitations by providing a large-scale perspective of distributed activity across the brain in a non-invasive manner. The present study used fMRI to characterize stimulus-evoked activity in auditory cortex of an anesthetized (ketamine/isoflurane) cat, focusing specifically on the blood-oxygen-level-dependent (BOLD) signal time course. Functional images were acquired for adult cats in a 7 T MRI scanner. To determine the BOLD signal time course, we presented 1s broadband noise bursts between widely spaced scan acquisitions at randomized delays (1-12 s in 1s increments) prior to each scan. Baseline trials in which no stimulus was presented were also acquired. Our results indicate that the BOLD response peaks at about 3.5s in primary auditory cortex (AI) and at about 4.5 s in non-primary areas (AII, PAF) of cat auditory cortex. The observed peak latency is within the range reported for humans and non-human primates (3-4 s). The time course of hemodynamic activity in cat auditory cortex also occurs on a comparatively shorter scale than in cat visual cortex. The results of this study will provide a foundation for future auditory fMRI studies in the cat to incorporate these hemodynamic response properties into appropriate analyses of cat auditory cortex. Copyright © 2012 Elsevier Inc. All rights reserved.

[MRI methods for pulmonary ventilation and perfusion imaging].

PubMed

Sommer, G; Bauman, G

2016-02-01

Separate assessment of respiratory mechanics, gas exchange and pulmonary circulation is essential for the diagnosis and therapy of pulmonary diseases. Due to the global character of the information obtained clinical lung function tests are often not sufficiently specific in the differential diagnosis or have a limited sensitivity in the detection of early pathological changes. The standard procedures of pulmonary imaging are computed tomography (CT) for depiction of the morphology as well as perfusion/ventilation scintigraphy and single photon emission computed tomography (SPECT) for functional assessment. Magnetic resonance imaging (MRI) with hyperpolarized gases, O2-enhanced MRI, MRI with fluorinated gases and Fourier decomposition MRI (FD-MRI) are available for assessment of pulmonary ventilation. For assessment of pulmonary perfusion dynamic contrast-enhanced MRI (DCE-MRI), arterial spin labeling (ASL) and FD-MRI can be used. Imaging provides a more precise insight into the pathophysiology of pulmonary function on a regional level. The advantages of MRI are a lack of ionizing radiation, which allows a protective acquisition of dynamic data as well as the high number of available contrasts and therefore accessible lung function parameters. Sufficient clinical data exist only for certain applications of DCE-MRI. For the other techniques, only feasibility studies and case series of different sizes are available. The clinical applicability of hyperpolarized gases is limited for technical reasons. The clinical application of the techniques described, except for DCE-MRI, should be restricted to scientific studies.

Studies in nonlinear optics and functional magnetic resonance imaging

NASA Astrophysics Data System (ADS)

Dai, Tehui

There are two parts in this thesis. The first part will involve a study in the anomalous dispersion phase matched second-harmonic generation, and the second part will be a study in functional magnetic resonance imaging (fMRI) and a biophysical model of the human muscle. In part I, we report on a series of tricyanovinylaniline chromophores for use as dopants in poled poly(methyl methacrylate) waveguides for anomalous-dispersion phase- matched second-harmonic generation. Second-harmonic generation measurements as a function of mode index confirmed anomalous dispersion phase-matching efficiencies as large as 245%/Wcm2 over a propagation length of ~35 μm. The waveguide coupling technique limited the interaction length. The photostability of the chromophores was measured directly and found to agree qualitatively with second-harmonic measurements over time and was found to be improved over previously reported materials. In part II, we designed a system that could record joint force and surface electromyography (EMG) simultaneously with fMRI data. I-Egh quality force and EMG data were obtained at the same time that excellent fMRI brain images were achieved. Using this system we determined the relationship between the fMRI-measured brain activation and the handgrip force, and between the fMRI-measured brain activation and the EMG of finger flexor muscles. We found that in the whole brain and in the majority of motor function-related cortical fields, the degree of muscle activation is directly proportional to the amplitude of the brain signal determined by the fMRI measurement. The similarity in the relationship between muscle output and fMRI signal in a number of brain areas suggests that multiple cortical fields are involved in controlling muscle force. The factors that may contribute to the fMRI signals are discussed. A biophysical twitch force model was developed to predict force response under electrical stimulation. Comparison between experimental and modeled force profiles, peak forces, and force duration shows excellent agreement between the model and the experimental data. It is concluded that the present model allows us to reproduce the main features of muscle activation under stimulation.

Motion Direction Biases and Decoding in Human Visual Cortex

PubMed Central

Wang, Helena X.; Merriam, Elisha P.; Freeman, Jeremy

2014-01-01

Functional magnetic resonance imaging (fMRI) studies have relied on multivariate analysis methods to decode visual motion direction from measurements of cortical activity. Above-chance decoding has been commonly used to infer the motion-selective response properties of the underlying neural populations. Moreover, patterns of reliable response biases across voxels that underlie decoding have been interpreted to reflect maps of functional architecture. Using fMRI, we identified a direction-selective response bias in human visual cortex that: (1) predicted motion-decoding accuracy; (2) depended on the shape of the stimulus aperture rather than the absolute direction of motion, such that response amplitudes gradually decreased with distance from the stimulus aperture edge corresponding to motion origin; and 3) was present in V1, V2, V3, but not evident in MT+, explaining the higher motion-decoding accuracies reported previously in early visual cortex. These results demonstrate that fMRI-based motion decoding has little or no dependence on the underlying functional organization of motion selectivity. PMID:25209297

Joint independent component analysis for simultaneous EEG-fMRI: principle and simulation.

PubMed

Moosmann, Matthias; Eichele, Tom; Nordby, Helge; Hugdahl, Kenneth; Calhoun, Vince D

2008-03-01

An optimized scheme for the fusion of electroencephalography and event related potentials with functional magnetic resonance imaging (BOLD-fMRI) data should simultaneously assess all available electrophysiologic and hemodynamic information in a common data space. In doing so, it should be possible to identify features of latent neural sources whose trial-to-trial dynamics are jointly reflected in both modalities. We present a joint independent component analysis (jICA) model for analysis of simultaneous single trial EEG-fMRI measurements from multiple subjects. We outline the general idea underlying the jICA approach and present results from simulated data under realistic noise conditions. Our results indicate that this approach is a feasible and physiologically plausible data-driven way to achieve spatiotemporal mapping of event related responses in the human brain.

Age and amyloid-related alterations in default network habituation to stimulus repetition

PubMed Central

Vannini, Patrizia; Hedden, Trey; Becker, John A.; Sullivan, Caroline; Putcha, Deepti; Rentz, Dorene; Johnson, Keith A.; Sperling, Reisa. A.

2011-01-01

The neural networks supporting encoding of new information are thought to decline with age, although mnemonic techniques such as repetition may enhance performance in older individuals. Accumulation of amyloid-β, one hallmark pathology of Alzheimer’s disease (AD), may contribute to functional alterations in memory networks measured with functional magnetic resonance imaging (fMRI) prior to onset of cognitive impairment. We investigated the effects of age and amyloid burden on fMRI activity in the default network and hippocampus during repetitive encoding. Older individuals, particularly those with high amyloid burden, demonstrated decreased task-induced deactivation in the posteromedial cortices during initial stimulus presentation and failed to modulate fMRI activity in response to repeated trials, whereas young subjects demonstrated a stepwise decrease in deactivation with repetition. The hippocampus demonstrated similar patterns across the groups, showing task-induced activity that decreased in response to repetition. These findings demonstrate that age and amyloid have dissociable functional effects on specific nodes within a distributed memory network, and suggest that functional brain changes may begin far in advance of symptomatic AD. PMID:21334099

Visual Learning Induces Changes in Resting-State fMRI Multivariate Pattern of Information.

PubMed

Guidotti, Roberto; Del Gratta, Cosimo; Baldassarre, Antonello; Romani, Gian Luca; Corbetta, Maurizio

2015-07-08

When measured with functional magnetic resonance imaging (fMRI) in the resting state (R-fMRI), spontaneous activity is correlated between brain regions that are anatomically and functionally related. Learning and/or task performance can induce modulation of the resting synchronization between brain regions. Moreover, at the neuronal level spontaneous brain activity can replay patterns evoked by a previously presented stimulus. Here we test whether visual learning/task performance can induce a change in the patterns of coded information in R-fMRI signals consistent with a role of spontaneous activity in representing task-relevant information. Human subjects underwent R-fMRI before and after perceptual learning on a novel visual shape orientation discrimination task. Task-evoked fMRI patterns to trained versus novel stimuli were recorded after learning was completed, and before the second R-fMRI session. Using multivariate pattern analysis on task-evoked signals, we found patterns in several cortical regions, as follows: visual cortex, V3/V3A/V7; within the default mode network, precuneus, and inferior parietal lobule; and, within the dorsal attention network, intraparietal sulcus, which discriminated between trained and novel visual stimuli. The accuracy of classification was strongly correlated with behavioral performance. Next, we measured multivariate patterns in R-fMRI signals before and after learning. The frequency and similarity of resting states representing the task/visual stimuli states increased post-learning in the same cortical regions recruited by the task. These findings support a representational role of spontaneous brain activity. Copyright © 2015 the authors 0270-6474/15/359786-13$15.00/0.

Decreased Functional Brain Activation in Friedreich Ataxia Using the Simon Effect Task

ERIC Educational Resources Information Center

Georgiou-Karistianis, N.; Akhlaghi, H.; Corben, L. A.; Delatycki, M. B.; Storey, E.; Bradshaw, J. L.; Egan, G. F.

2012-01-01

The present study applied the Simon effect task to examine the pattern of functional brain reorganization in individuals with Friedreich ataxia (FRDA), using functional magnetic resonance imaging (fMRI). Thirteen individuals with FRDA and 14 age and sex matched controls participated, and were required to respond to either congruent or incongruent…

WE-EF-BRD-00: New Developments in Hybrid MR-Treatment: Applications

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

NONE

2015-06-15

MRI-guided treatment is a growing area of medicine, particularly in radiotherapy and surgery. The exquisite soft tissue anatomic contrast offered by MRI, along with functional imaging, makes the use of MRI during therapeutic procedures very attractive. Challenging the utility of MRI in the therapy room are many issues including the physics of MRI and the impact on the environment and therapeutic instruments, the impact of the room and instruments on the MRI; safety, space, design and cost. In this session, the applications and challenges of MRI-guided treatment will be described. The session format is: Past, present and future: MRI-guided radiotherapymore » from 2005 to 2025: Jan Lagendijk Battling Maxwell’s equations: Physics challenges and solutions for hybrid MRI systems: Paul Keall I want it now!: Advances in MRI acquisition, reconstruction and the use of priors to enable fast anatomic and physiologic imaging to inform guidance and adaptation decisions: Yanle Hu MR in the OR: The growth and applications of MRI for interventional radiology and surgery: Rebecca Fahrig Learning Objectives: To understand the history and trajectory of MRI-guided radiotherapy To understand the challenges of integrating MR imaging systems with linear accelerators To understand the latest in fast MRI methods to enable the visualisation of anatomy and physiology on radiotherapy treatment timescales To understand the growing role and challenges of MRI for image-guided surgical procedures My disclosures are publicly available and updated at: http://sydney.edu.au/medicine/radiation-physics/about-us/disclosures.php.« less

Diffusion Tensor Imaging and Resting-State Functional MRI-Scanning in 5- and 6-Year-Old Children: Training Protocol and Motion Assessment

PubMed Central

Theys, Catherine; Wouters, Jan; Ghesquière, Pol

2014-01-01

Advanced Magnetic Resonance Imaging (MRI) techniques such as Diffusion Tensor Imaging (DTI) and resting-state functional MRI (rfMRI) are widely used to study structural and functional neural connectivity. However, as these techniques are highly sensitive to motion artifacts and require a considerable amount of time for image acquisition, successful acquisition of these images can be challenging to complete with certain populations. This is especially true for young children. This paper describes a new approach termed the ‘submarine protocol’, designed to prepare 5- and 6-year-old children for advanced MRI scanning. The submarine protocol aims to ensure that successful scans can be acquired in a time- and resource-efficient manner, without the need for sedation. This manuscript outlines the protocol and details its outcomes, as measured through the number of children who completed the scanning procedure and analysis of the degree of motion present in the acquired images. Seventy-six children aged between 5.8 and 6.9 years were trained using the submarine protocol and subsequently underwent DTI and rfMRI scanning. After completing the submarine protocol, 75 of the 76 children (99%) completed their DTI-scan and 72 children (95%) completed the full 35-minute scan session. Results of diffusion data, acquired in 75 children, showed that the motion in 60 of the scans (80%) did not exceed the threshold for excessive motion. In the rfMRI scans, this was the case for 62 of the 71 scans (87%). When placed in the context of previous studies, the motion data of the 5- and 6-year-old children reported here were as good as, or better than those previously reported for groups of older children (i.e., 8-year-olds). Overall, this study shows that the submarine protocol can be used successfully to acquire DTI and rfMRI scans in 5 and 6-year-old children, without the need for sedation or lengthy training procedures. PMID:24718364

Computing moment to moment BOLD activation for real-time neurofeedback

PubMed Central

Hinds, Oliver; Ghosh, Satrajit; Thompson, Todd W.; Yoo, Julie J.; Whitfield-Gabrieli, Susan; Triantafyllou, Christina; Gabrieli, John D.E.

2013-01-01

Estimating moment to moment changes in blood oxygenation level dependent (BOLD) activation levels from functional magnetic resonance imaging (fMRI) data has applications for learned regulation of regional activation, brain state monitoring, and brain-machine interfaces. In each of these contexts, accurate estimation of the BOLD signal in as little time as possible is desired. This is a challenging problem due to the low signal-to-noise ratio of fMRI data. Previous methods for real-time fMRI analysis have either sacrificed the ability to compute moment to moment activation changes by averaging several acquisitions into a single activation estimate or have sacrificed accuracy by failing to account for prominent sources of noise in the fMRI signal. Here we present a new method for computing the amount of activation present in a single fMRI acquisition that separates moment to moment changes in the fMRI signal intensity attributable to neural sources from those due to noise, resulting in a feedback signal more reflective of neural activation. This method computes an incremental general linear model fit to the fMRI timeseries, which is used to calculate the expected signal intensity at each new acquisition. The difference between the measured intensity and the expected intensity is scaled by the variance of the estimator in order to transform this residual difference into a statistic. Both synthetic and real data were used to validate this method and compare it to the only other published real-time fMRI method. PMID:20682350

MRI of plants and foods

NASA Astrophysics Data System (ADS)

Van As, Henk; van Duynhoven, John

2013-04-01

The importance and prospects for MRI as applied to intact plants and to foods are presented in view of one of humanity's most pressing concerns, the sustainable and healthy feeding of a worldwide increasing population. Intact plants and foods have in common that their functionality is determined by complex multiple length scale architectures. Intact plants have an additional level of complexity since they are living systems which critically depend on transport and signalling processes between and within tissues and organs. The combination of recent cutting-edge technical advances and integration of MRI accessible parameters has the perspective to contribute to breakthroughs in understanding complex regulatory plant performance mechanisms. In food science and technology MRI allows for quantitative multi-length scale structural assessment of food systems, non-invasive monitoring of heat and mass transport during shelf-life and processing, and for a unique view on food properties under shear. These MRI applications are powerful enablers of rationally (re)designed food formulations and processes. Limitations and bottlenecks of the present plant and food MRI methods are mainly related to short T2 values and susceptibility artefacts originating from small air spaces in tissues/materials. We envisage cross-fertilisation of solutions to overcome these hurdles in MRI applications in plants and foods. For both application areas we witness a development where MRI is moving from highly specialised equipment to mobile and downscaled versions to be used by a broad user base in the field, greenhouse, food laboratory or factory.

Cell tracking with caged xenon: using cryptophanes as MRI reporters upon cellular internalization.

PubMed

Klippel, Stefan; Döpfert, Jörg; Jayapaul, Jabadurai; Kunth, Martin; Rossella, Federica; Schnurr, Matthias; Witte, Christopher; Freund, Christian; Schröder, Leif

2014-01-07

Caged xenon has great potential in overcoming sensitivity limitations for solution-state NMR detection of dilute molecules. However, no application of such a system as a magnetic resonance imaging (MRI) contrast agent has yet been performed with live cells. We demonstrate MRI localization of cells labeled with caged xenon in a packed-bed bioreactor working under perfusion with hyperpolarized-xenon-saturated medium. Xenon hosts enable NMR/MRI experiments with switchable contrast and selectivity for cell-associated versus unbound cages. We present MR images with 10(3) -fold sensitivity enhancement for cell-internalized, dual-mode (fluorescence/MRI) xenon hosts at low micromolar concentrations. Our results illustrate the capability of functionalized xenon to act as a highly sensitive cell tracer for MRI detection even without signal averaging. The method will bridge the challenging gap for translation to in vivo studies for the optimization of targeted biosensors and their multiplexing applications. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Comparison of fMRI data from passive listening and active-response story processing tasks in children.

PubMed

Vannest, Jennifer J; Karunanayaka, Prasanna R; Altaye, Mekibib; Schmithorst, Vincent J; Plante, Elena M; Eaton, Kenneth J; Rasmussen, Jerod M; Holland, Scott K

2009-04-01

To use functional MRI (fMRI) methods to visualize a network of auditory and language-processing brain regions associated with processing an aurally-presented story. We compare a passive listening (PL) story paradigm to an active-response (AR) version including online performance monitoring and a sparse acquisition technique. Twenty children (ages 11-13 years) completed PL and AR story processing tasks. The PL version presented alternating 30-second blocks of stories and tones; the AR version presented story segments, comprehension questions, and 5-second tone sequences, with fMRI acquisitions between stimuli. fMRI data was analyzed using a general linear model approach and paired t-test identifying significant group activation. Both tasks showed activation in the primary auditory cortex, superior temporal gyrus bilaterally, and left inferior frontal gyrus (IFG). The AR task demonstrated more extensive activation, including the dorsolateral prefrontal cortex and anterior/posterior cingulate cortex. Comparison of effect size in each paradigm showed a larger effect for the AR paradigm in a left inferior frontal region-of-interest (ROI). Activation patterns for story processing in children are similar in PL and AR tasks. Increases in extent and magnitude of activation in the AR task are likely associated with memory and attention resources engaged across acquisition intervals.

Study of MRI in stratified viscous plasma configuration

NASA Astrophysics Data System (ADS)

Carlevaro, Nakia; Montani, Giovanni; Renzi, Fabrizio

2017-02-01

We analyze the morphology of the magneto-rotational instability (MRI) for a stratified viscous plasma disk configuration in differential rotation, taking into account the so-called corotation theorem for the background profile. In order to select the intrinsic Alfvénic nature of MRI, we deal with an incompressible plasma and we adopt a formulation of the local perturbation analysis based on the use of the magnetic flux function as a dynamical variable. Our study outlines, as consequence of the corotation condition, a marked asymmetry of the MRI with respect to the equatorial plane, particularly evident in a complete damping of the instability over a positive critical height on the equatorial plane. We also emphasize how such a feature is already present (although less pronounced) even in the ideal case, restoring a dependence of the MRI on the stratified morphology of the gravitational field.

Low back pain: an assessment using positional MRI and MDT.

PubMed

Hedberg, Karen; Alexander, Lyndsay A; Cooper, Kay; Hancock, Elizabeth; Ross, Jenny; Smith, Francis W

2013-04-01

Current guidelines advise against the use of routine imaging for low back pain. Positional MRI can provide enhanced assessment of the lumbar spine in functionally loaded positions which are often relevant to the presenting clinical symptoms. The purpose of this case report is to highlight the use of positional MRI in the assessment and classification of a subject with low back pain. A low back pain subject underwent a Mechanical Diagnosis and Therapy (MDT) assessment and positional MRI scan of the lumbar spine. The MDT assessment classified the subject as "other" since the subjective history indicated a possible posterior derangement whilst the objective assessment indicated a possible anterior derangement. Positional MRI scanning in flexed, upright and extended sitting postures confirmed the MDT assessment findings to reveal a dynamic spinal stenosis which reduced in flexion and increased in extension. Copyright © 2012 Elsevier Ltd. All rights reserved.

NEURAL SUBSTRATES OF CUE-REACTIVITY: ASSOCIATION WITH TREATMENT OUTCOMES AND RELAPSE

PubMed Central

Courtney, Kelly E.; Schacht, Joseph P.; Hutchison, Kent; Roche, Daniel J.O.; Ray, Lara A.

2016-01-01

Given the strong evidence for neurological alterations at the basis of drug dependence, functional magnetic resonance imaging (fMRI) represents an important tool in the clinical neuroscience of addiction. fMRI cue-reactivity paradigms represent an ideal platform to probe the involvement of neurobiological pathways subserving the reward/motivation system in addiction and potentially offer a translational mechanism by which interventions and behavioral predictions can be tested. Thus, this review summarizes the research that has applied fMRI cue-reactivity paradigms to the study of adult substance use disorder treatment responses. Studies utilizing fMRI cue-reactivity paradigms for the prediction of relapse, and as a means to investigate psychosocial and pharmacological treatment effects on cue-elicited brain activation are presented within four primary categories of substances: alcohol, nicotine, cocaine, and opioids. Lastly, suggestions for how to leverage fMRI technology to advance addiction science and treatment development are provided. PMID:26435524

Conductors for commercial MRI magnets beyond NbTi: requirements and challenges.

PubMed

Parizh, Michael; Lvovsky, Yuri; Sumption, Michael

2017-01-01

Magnetic Resonance Imaging (MRI), a powerful medical diagnostic tool, is the largest commercial application of superconductivity. The superconducting magnet is the largest and most expensive component of an MRI system. The magnet configuration is determined by competing requirements including optimized functional performance, patient comfort, ease of siting in a hospital environment, minimum acquisition and lifecycle cost including service. In this paper, we analyze conductor requirements for commercial MRI magnets beyond traditional NbTi conductors, while avoiding links to a particular magnet configuration or design decisions. Potential conductor candidates include MgB 2 , ReBCO and BSCCO options. The analysis shows that no MRI-ready non-NbTi conductor is commercially available at the moment. For some conductors, MRI specifications will be difficult to achieve in principle. For others, cost is a key barrier. In some cases, the prospects for developing an MRI-ready conductor are more favorable, but significant developments are still needed. The key needs include the development of, or significant improvements in: (a) conductors specifically designed for MRI applications, with form-fit-and-function readily integratable into the present MRI magnet technology with minimum modifications. Preferably, similar conductors should be available from multiple vendors; (b) conductors with improved quench characteristics, i.e. the ability to carry significant current without damage while in the resistive state; (c) insulation which is compatible with manufacturing and refrigeration technologies; (d) dramatic increases in production and long-length quality control, including large-volume conductor manufacturing technology. In-situ MgB 2 is, perhaps, the closest to meeting commercial and technical requirements to become suitable for commercial MRI. Conductor technology is an important, but not the only, issue in introduction of HTS / MgB 2 conductor into commercial MRI magnets. These new conductors, even when they meet the above requirements, will likely require numerous modifications and developments in the associated magnet technology.

Conductors for commercial MRI magnets beyond NbTi: requirements and challenges

NASA Astrophysics Data System (ADS)

Parizh, Michael; Lvovsky, Yuri; Sumption, Michael

2017-01-01

Magnetic resonance imaging (MRI), a powerful medical diagnostic tool, is the largest commercial application of superconductivity. The superconducting magnet is the largest and most expensive component of an MRI system. The magnet configuration is determined by competing requirements including optimized functional performance, patient comfort, ease of siting in a hospital environment, minimum acquisition and lifecycle cost including service. In this paper, we analyze conductor requirements for commercial MRI magnets beyond traditional NbTi conductors, while avoiding links to a particular magnet configuration or design decisions. Potential conductor candidates include MgB2, ReBCO and BSCCO options. The analysis shows that no MRI-ready non-NbTi conductor is commercially available at the moment. For some conductors, MRI specifications will be difficult to achieve in principle. For others, cost is a key barrier. In some cases, the prospects for developing an MRI-ready conductor are more favorable, but significant developments are still needed. The key needs include the development of, or significant improvements in: (a) conductors specifically designed for MRI applications, with form-fit-and-function readily integratable into the present MRI magnet technology with minimum modifications. Preferably, similar conductors should be available from multiple vendors; (b) conductors with improved quench characteristics, i.e. the ability to carry significant current without damage while in the resistive state; (c) insulation which is compatible with manufacturing and refrigeration technologies; (d) dramatic increases in production and long-length quality control, including large-volume conductor manufacturing technology. In-situ MgB2 is, perhaps, the closest to meeting commercial and technical requirements to become suitable for commercial MRI. Conductor technology is an important, but not the only, issue in introduction of HTS/MgB2 conductor into commercial MRI magnets. These new conductors, even when they meet the above requirements, will likely require numerous modifications and developments in the associated magnet technology.

Conductors for commercial MRI magnets beyond NbTi: requirements and challenges

PubMed Central

Parizh, Michael; Lvovsky, Yuri; Sumption, Michael

2016-01-01

Magnetic Resonance Imaging (MRI), a powerful medical diagnostic tool, is the largest commercial application of superconductivity. The superconducting magnet is the largest and most expensive component of an MRI system. The magnet configuration is determined by competing requirements including optimized functional performance, patient comfort, ease of siting in a hospital environment, minimum acquisition and lifecycle cost including service. In this paper, we analyze conductor requirements for commercial MRI magnets beyond traditional NbTi conductors, while avoiding links to a particular magnet configuration or design decisions. Potential conductor candidates include MgB2, ReBCO and BSCCO options. The analysis shows that no MRI-ready non-NbTi conductor is commercially available at the moment. For some conductors, MRI specifications will be difficult to achieve in principle. For others, cost is a key barrier. In some cases, the prospects for developing an MRI-ready conductor are more favorable, but significant developments are still needed. The key needs include the development of, or significant improvements in: (a) conductors specifically designed for MRI applications, with form-fit-and-function readily integratable into the present MRI magnet technology with minimum modifications. Preferably, similar conductors should be available from multiple vendors; (b) conductors with improved quench characteristics, i.e. the ability to carry significant current without damage while in the resistive state; (c) insulation which is compatible with manufacturing and refrigeration technologies; (d) dramatic increases in production and long-length quality control, including large-volume conductor manufacturing technology. In-situ MgB2 is, perhaps, the closest to meeting commercial and technical requirements to become suitable for commercial MRI. Conductor technology is an important, but not the only, issue in introduction of HTS / MgB2 conductor into commercial MRI magnets. These new conductors, even when they meet the above requirements, will likely require numerous modifications and developments in the associated magnet technology. PMID:28626340

Regional Homogeneity Predicts Creative Insight: A Resting-State fMRI Study.

PubMed

Lin, Jiabao; Cui, Xuan; Dai, Xiaoying; Mo, Lei

2018-01-01

Creative insight plays an important role in our daily life. Previous studies have investigated the neural correlates of creative insight by functional magnetic resonance imaging (fMRI), however, the intrinsic resting-state brain activity associated with creative insight is still unclear. In the present study, we used regional homogeneity (ReHo) as an index in resting-state fMRI (rs-fMRI) to identify brain regions involved in individual differences in creative insight, which was compued by the response time (RT) of creative Chinese character chunk decomposition. The findings indicated that ReHo in the anterior cingulate cortex (ACC)/caudate nucleus (CN) and angular gyrus (AG)/superior temporal gyrus (STG)/inferior parietal lobe (IPL) negatively predicted creative insight. Furthermore, these findings suggested that spontaneous brain activity in multiple regions related to breaking and establishing mental sets, goal-directed solutions exploring, shifting attention, forming new associations and emotion experience contributes to creative insight. In conclusion, the present study provides new evidence to further understand the cognitive processing and neural correlates of creative insight.

Disrupted Cerebro-cerebellar Intrinsic Functional Connectivity in Young Adults with High-functioning Autism Spectrum Disorder: A Data-driven, Whole-brain, High Temporal Resolution fMRI Study.

PubMed

Arnold Anteraper, Sheeba; Guell, Xavier; D'Mello, Anila; Joshi, Neha; Whitfield-Gabrieli, Susan; Joshi, Gagan

2018-06-13

To examine the resting-state functional-connectivity (RsFc) in young adults with high-functioning autism spectrum disorder (HF-ASD) using state-of-the-art fMRI data acquisition and analysis techniques. Simultaneous multi-slice, high temporal resolution fMRI acquisition; unbiased whole-brain connectome-wide multivariate pattern analysis (MVPA) techniques for assessing RsFc; and post-hoc whole-brain seed-to-voxel analyses using MVPA results as seeds. MVPA revealed two clusters of abnormal connectivity in the cerebellum. Whole-brain seed-based functional connectivity analyses informed by MVPA-derived clusters showed significant under connectivity between the cerebellum and social, emotional, and language brain regions in the HF-ASD group compared to healthy controls. The results we report are coherent with existing structural, functional, and RsFc literature in autism, extend previous literature reporting cerebellar abnormalities in the neuropathology of autism, and highlight the cerebellum as a potential target for therapeutic, diagnostic, predictive, and prognostic developments in ASD. The description of functional connectivity abnormalities using whole-brain, data-driven analyses as reported in the present study may crucially advance the development of ASD biomarkers, targets for therapeutic interventions, and neural predictors for measuring treatment response.

The secret lives of experiments: methods reporting in the fMRI literature.

PubMed

Carp, Joshua

2012-10-15

Replication of research findings is critical to the progress of scientific understanding. Accordingly, most scientific journals require authors to report experimental procedures in sufficient detail for independent researchers to replicate their work. To what extent do research reports in the functional neuroimaging literature live up to this standard? The present study evaluated methods reporting and methodological choices across 241 recent fMRI articles. Many studies did not report critical methodological details with regard to experimental design, data acquisition, and analysis. Further, many studies were underpowered to detect any but the largest statistical effects. Finally, data collection and analysis methods were highly flexible across studies, with nearly as many unique analysis pipelines as there were studies in the sample. Because the rate of false positive results is thought to increase with the flexibility of experimental designs, the field of functional neuroimaging may be particularly vulnerable to false positives. In sum, the present study documented significant gaps in methods reporting among fMRI studies. Improved methodological descriptions in research reports would yield significant benefits for the field. Copyright © 2012 Elsevier Inc. All rights reserved.

Functional connectomics from resting-state fMRI

PubMed Central

Smith, Stephen M; Vidaurre, Diego; Beckmann, Christian F; Glasser, Matthew F; Jenkinson, Mark; Miller, Karla L; Nichols, Thomas E; Robinson, Emma; Salimi-Khorshidi, Gholamreza; Woolrich, Mark W; Barch, Deanna M; Uğurbil, Kamil; Van Essen, David C

2014-01-01

Spontaneous fluctuations in activity in different parts of the brain can be used to study functional brain networks. We review the use of resting-state functional MRI for the purpose of mapping the macroscopic functional connectome. After describing MRI acquisition and image processing methods commonly used to generate data in a form amenable to connectomics network analysis, we discuss different approaches for estimating network structure from that data. Finally, we describe new possibilities resulting from the high-quality rfMRI data being generated by the Human Connectome Project, and highlight some upcoming challenges in functional connectomics. PMID:24238796

Design and Evaluation of a Cable-Driven fMRI-Compatible Haptic Interface to Investigate Precision Grip Control

PubMed Central

Vigaru, Bogdan; Sulzer, James; Gassert, Roger

2016-01-01

Our hands and fingers are involved in almost all activities of daily living and, as such, have a disproportionately large neural representation. Functional magnetic resonance imaging investigations into the neural control of the hand have revealed great advances, but the harsh MRI environment has proven to be a challenge to devices capable of delivering a large variety of stimuli necessary for well-controlled studies. This paper presents a fMRI-compatible haptic interface to investigate the neural mechanisms underlying precision grasp control. The interface, located at the scanner bore, is controlled remotely through a shielded electromagnetic actuation system positioned at the end of the scanner bed and then through a high stiffness, low inertia cable transmission. We present the system design, taking into account requirements defined by the biomechanics and dynamics of the human hand, as well as the fMRI environment. Performance evaluation revealed a structural stiffness of 3.3 N/mm, renderable forces up to 94 N, and a position control bandwidth of at least 19 Hz. MRI-compatibility tests showed no degradation in the operation of the haptic interface or the image quality. A preliminary fMRI experiment during a pilot study validated the usability of the haptic interface, illustrating the possibilities offered by this device. PMID:26441454

Development of a PET Scanner for Simultaneously Imaging Small Animals with MRI and PET

PubMed Central

Thompson, Christopher J; Goertzen, Andrew L; Thiessen, Jonathan D; Bishop, Daryl; Stortz, Greg; Kozlowski, Piotr; Retière, Fabrice; Zhang, Xuezhu; Sossi, Vesna

2014-01-01

Recently, positron emission tomography (PET) is playing an increasingly important role in the diagnosis and staging of cancer. Combined PET and X-ray computed tomography (PET-CT) scanners are now the modality of choice in cancer treatment planning. More recently, the combination of PET and magnetic resonance imaging (MRI) is being explored in many sites. Combining PET and MRI has presented many challenges since the photo-multiplier tubes (PMT) in PET do not function in high magnetic fields, and conventional PET detectors distort MRI images. Solid state light sensors like avalanche photo-diodes (APDs) and more recently silicon photo-multipliers (SiPMs) are much less sensitive to magnetic fields thus easing the compatibility issues. This paper presents the results of a group of Canadian scientists who are developing a PET detector ring which fits inside a high field small animal MRI scanner with the goal of providing simultaneous PET and MRI images of small rodents used in pre-clinical medical research. We discuss the evolution of both the crystal blocks (which detect annihilation photons from positron decay) and the SiPM array performance in the last four years which together combine to deliver significant system performance in terms of speed, energy and timing resolution. PMID:25120157

Resting-state functional magnetic resonance imaging in hepatic encephalopathy: current status and perspectives.

PubMed

Zhang, Long Jiang; Wu, Shengyong; Ren, Jiaqian; Lu, Guang Ming

2014-09-01

Hepatic encephalopathy (HE) is a neuropsychiatric syndrome which develops in patients with severe liver diseases and/or portal-systemic shunting. Minimal HE, the earliest manifestation of HE, has drawn increasing attention in the last decade. Minimal HE is associated with a series of brain functional changes, such as attention, working memory, and so on. Blood oxygen level dependent (BOLD) functional MRI (fMRI), especially resting-state fMRI has been used to explore the brain functional changes of HE, yielding important insights for understanding pathophysiological mechanisms and functional reorganization of HE. This paper briefly reviews the principles of BOLD fMRI, potential applications of resting-state fMRI with advanced post-processing algorithms such as regional homogeneity, amplitude of low frequency fluctuation, functional connectivity and future research perspective in this field.

HAFNI-enabled largescale platform for neuroimaging informatics (HELPNI).

PubMed

Makkie, Milad; Zhao, Shijie; Jiang, Xi; Lv, Jinglei; Zhao, Yu; Ge, Bao; Li, Xiang; Han, Junwei; Liu, Tianming

Tremendous efforts have thus been devoted on the establishment of functional MRI informatics systems that recruit a comprehensive collection of statistical/computational approaches for fMRI data analysis. However, the state-of-the-art fMRI informatics systems are especially designed for specific fMRI sessions or studies of which the data size is not really big, and thus has difficulty in handling fMRI 'big data.' Given the size of fMRI data are growing explosively recently due to the advancement of neuroimaging technologies, an effective and efficient fMRI informatics system which can process and analyze fMRI big data is much needed. To address this challenge, in this work, we introduce our newly developed informatics platform, namely, 'HAFNI-enabled largescale platform for neuroimaging informatics (HELPNI).' HELPNI implements our recently developed computational framework of sparse representation of whole-brain fMRI signals which is called holistic atlases of functional networks and interactions (HAFNI) for fMRI data analysis. HELPNI provides integrated solutions to archive and process large-scale fMRI data automatically and structurally, to extract and visualize meaningful results information from raw fMRI data, and to share open-access processed and raw data with other collaborators through web. We tested the proposed HELPNI platform using publicly available 1000 Functional Connectomes dataset including over 1200 subjects. We identified consistent and meaningful functional brain networks across individuals and populations based on resting state fMRI (rsfMRI) big data. Using efficient sampling module, the experimental results demonstrate that our HELPNI system has superior performance than other systems for large-scale fMRI data in terms of processing and storing the data and associated results much faster.

HAFNI-enabled largescale platform for neuroimaging informatics (HELPNI).

PubMed

Makkie, Milad; Zhao, Shijie; Jiang, Xi; Lv, Jinglei; Zhao, Yu; Ge, Bao; Li, Xiang; Han, Junwei; Liu, Tianming

2015-12-01

Tremendous efforts have thus been devoted on the establishment of functional MRI informatics systems that recruit a comprehensive collection of statistical/computational approaches for fMRI data analysis. However, the state-of-the-art fMRI informatics systems are especially designed for specific fMRI sessions or studies of which the data size is not really big, and thus has difficulty in handling fMRI 'big data.' Given the size of fMRI data are growing explosively recently due to the advancement of neuroimaging technologies, an effective and efficient fMRI informatics system which can process and analyze fMRI big data is much needed. To address this challenge, in this work, we introduce our newly developed informatics platform, namely, 'HAFNI-enabled largescale platform for neuroimaging informatics (HELPNI).' HELPNI implements our recently developed computational framework of sparse representation of whole-brain fMRI signals which is called holistic atlases of functional networks and interactions (HAFNI) for fMRI data analysis. HELPNI provides integrated solutions to archive and process large-scale fMRI data automatically and structurally, to extract and visualize meaningful results information from raw fMRI data, and to share open-access processed and raw data with other collaborators through web. We tested the proposed HELPNI platform using publicly available 1000 Functional Connectomes dataset including over 1200 subjects. We identified consistent and meaningful functional brain networks across individuals and populations based on resting state fMRI (rsfMRI) big data. Using efficient sampling module, the experimental results demonstrate that our HELPNI system has superior performance than other systems for large-scale fMRI data in terms of processing and storing the data and associated results much faster.

Transplantation of human immature dental pulp stem cell in dogs with chronic spinal cord injury.

PubMed

Feitosa, Matheus Levi Tajra; Sarmento, Carlos Alberto Palmeira; Bocabello, Renato Zonzini; Beltrão-Braga, Patrícia Cristina Baleeiro; Pignatari, Graciela Conceição; Giglio, Robson Fortes; Miglino, Maria Angelica; Orlandin, Jéssica Rodrigues; Ambrósio, Carlos Eduardo

2017-07-01

To investigate the therapeutic potential of human immature dental pulp stem cells in the treatment of chronic spinal cord injury in dogs. Three dogs of different breeds with chronic SCI were presented as animal clinical cases. Human immature dental pulp stem cells were injected at three points into the spinal cord, and the animals were evaluated by limb function and magnetic resonance imaging (MRI) pre and post-operative. There was significant improvement from the limb function evaluated by Olby Scale, though it was not supported by the imaging data provided by MRI and clinical sign and evaluation. Human dental pulp stem cell therapy presents promising clinical results in dogs with chronic spinal cord injuries, if used in association with physical therapy.

Detection of Brain Reorganization in Pediatric Multiple Sclerosis Using Functional MRI

DTIC Science & Technology

2015-10-01

accomplish this, we apply comparative assessments of fMRI mappings of language, memory , and motor function, and performance on clinical neurocognitive...community at a target rate of 13 volunteers per quarter period; acquire fMRI data for language, memory , and visual-motor functions (months 3-12). c...consensus fMRI activation maps for language, memory , and visual-motor tasks (months 8-12). f) Subtask 1f. Prepare publication to disseminate our

An automated method for identifying artifact in independent component analysis of resting-state FMRI.

PubMed

Bhaganagarapu, Kaushik; Jackson, Graeme D; Abbott, David F

2013-01-01

An enduring issue with data-driven analysis and filtering methods is the interpretation of results. To assist, we present an automatic method for identification of artifact in independent components (ICs) derived from functional MRI (fMRI). The method was designed with the following features: does not require temporal information about an fMRI paradigm; does not require the user to train the algorithm; requires only the fMRI images (additional acquisition of anatomical imaging not required); is able to identify a high proportion of artifact-related ICs without removing components that are likely to be of neuronal origin; can be applied to resting-state fMRI; is automated, requiring minimal or no human intervention. We applied the method to a MELODIC probabilistic ICA of resting-state functional connectivity data acquired in 50 healthy control subjects, and compared the results to a blinded expert manual classification. The method identified between 26 and 72% of the components as artifact (mean 55%). About 0.3% of components identified as artifact were discordant with the manual classification; retrospective examination of these ICs suggested the automated method had correctly identified these as artifact. We have developed an effective automated method which removes a substantial number of unwanted noisy components in ICA analyses of resting-state fMRI data. Source code of our implementation of the method is available.

Encoding and immediate retrieval tasks in patients with epilepsy: A functional MRI study of verbal and visual memory.

PubMed

Saddiki, Najat; Hennion, Sophie; Viard, Romain; Ramdane, Nassima; Lopes, Renaud; Baroncini, Marc; Szurhaj, William; Reyns, Nicolas; Pruvo, Jean Pierre; Delmaire, Christine

2018-05-01

Medial lobe temporal structures and more specifically the hippocampus play a decisive role in episodic memory. Most of the memory functional magnetic resonance imaging (fMRI) studies evaluate the encoding phase; the retrieval phase being performed outside the MRI. We aimed to determine the ability to reveal greater hippocampal fMRI activations during retrieval phase. Thirty-five epileptic patients underwent a two-step memory fMRI. During encoding phase, subjects were requested to identify the feminine or masculine gender of faces and words presented, in order to encourage stimulus encoding. One hour after, during retrieval phase, subjects had to recognize the word and face. We used an event-related design to identify hippocampal activations. There was no significant difference between patients with left temporal lobe epilepsy, patients with right temporal lobe epilepsy and patients with extratemporal lobe epilepsy on verbal and visual learning task. For words, patients demonstrated significantly more bilateral hippocampal activation for retrieval task than encoding task and when the tasks were associated than during encoding alone. Significant difference was seen between face-encoding alone and face retrieval alone. This study demonstrates the essential contribution of the retrieval task during a fMRI memory task but the number of patients with hippocampal activations was greater when the two tasks were taken into account. Copyright © 2018. Published by Elsevier Masson SAS.

Improved spatial accuracy of functional maps in the rat olfactory bulb using supervised machine learning approach.

PubMed

Murphy, Matthew C; Poplawsky, Alexander J; Vazquez, Alberto L; Chan, Kevin C; Kim, Seong-Gi; Fukuda, Mitsuhiro

2016-08-15

Functional MRI (fMRI) is a popular and important tool for noninvasive mapping of neural activity. As fMRI measures the hemodynamic response, the resulting activation maps do not perfectly reflect the underlying neural activity. The purpose of this work was to design a data-driven model to improve the spatial accuracy of fMRI maps in the rat olfactory bulb. This system is an ideal choice for this investigation since the bulb circuit is well characterized, allowing for an accurate definition of activity patterns in order to train the model. We generated models for both cerebral blood volume weighted (CBVw) and blood oxygen level dependent (BOLD) fMRI data. The results indicate that the spatial accuracy of the activation maps is either significantly improved or at worst not significantly different when using the learned models compared to a conventional general linear model approach, particularly for BOLD images and activity patterns involving deep layers of the bulb. Furthermore, the activation maps computed by CBVw and BOLD data show increased agreement when using the learned models, lending more confidence to their accuracy. The models presented here could have an immediate impact on studies of the olfactory bulb, but perhaps more importantly, demonstrate the potential for similar flexible, data-driven models to improve the quality of activation maps calculated using fMRI data. Copyright © 2016 Elsevier Inc. All rights reserved.

Automated processing pipeline for neonatal diffusion MRI in the developing Human Connectome Project.

PubMed

Bastiani, Matteo; Andersson, Jesper L R; Cordero-Grande, Lucilio; Murgasova, Maria; Hutter, Jana; Price, Anthony N; Makropoulos, Antonios; Fitzgibbon, Sean P; Hughes, Emer; Rueckert, Daniel; Victor, Suresh; Rutherford, Mary; Edwards, A David; Smith, Stephen M; Tournier, Jacques-Donald; Hajnal, Joseph V; Jbabdi, Saad; Sotiropoulos, Stamatios N

2018-05-28

The developing Human Connectome Project is set to create and make available to the scientific community a 4-dimensional map of functional and structural cerebral connectivity from 20 to 44 weeks post-menstrual age, to allow exploration of the genetic and environmental influences on brain development, and the relation between connectivity and neurocognitive function. A large set of multi-modal MRI data from fetuses and newborn infants is currently being acquired, along with genetic, clinical and developmental information. In this overview, we describe the neonatal diffusion MRI (dMRI) image processing pipeline and the structural connectivity aspect of the project. Neonatal dMRI data poses specific challenges, and standard analysis techniques used for adult data are not directly applicable. We have developed a processing pipeline that deals directly with neonatal-specific issues, such as severe motion and motion-related artefacts, small brain sizes, high brain water content and reduced anisotropy. This pipeline allows automated analysis of in-vivo dMRI data, probes tissue microstructure, reconstructs a number of major white matter tracts, and includes an automated quality control framework that identifies processing issues or inconsistencies. We here describe the pipeline and present an exemplar analysis of data from 140 infants imaged at 38-44 weeks post-menstrual age. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

The effect of fMRI task combinations on determining the hemispheric dominance of language functions.

PubMed

Niskanen, Eini; Könönen, Mervi; Villberg, Ville; Nissi, Mikko; Ranta-Aho, Perttu; Säisänen, Laura; Karjalainen, Pasi; Aikiä, Marja; Kälviäinen, Reetta; Mervaala, Esa; Vanninen, Ritva

2012-04-01

The purpose of this study is to establish the most suitable combination of functional magnetic resonance imaging (fMRI) language tasks for clinical use in determining language dominance and to define the variability in laterality index (LI) and activation power between different combinations of language tasks. Activation patterns of different fMRI analyses of five language tasks (word generation, responsive naming, letter task, sentence comprehension, and word pair) were defined for 20 healthy volunteers (16 right-handed). LIs and sums of T values were calculated for each task separately and for four combinations of tasks in predefined regions of interest. Variability in terms of activation power and lateralization was defined in each analysis. In addition, the visual assessment of lateralization of language functions based on the individual fMRI activation maps was conducted by an experienced neuroradiologist. A combination analysis of word generation, responsive naming, and sentence comprehension was the most suitable in terms of activation power, robustness to detect essential language areas, and scanning time. In general, combination analyses of the tasks provided higher overall activation levels than single tasks and reduced the number of outlier voxels disturbing the calculation of LI. A combination of auditory and visually presented tasks that activate different aspects of language functions with sufficient activation power may be a useful task battery for determining language dominance in patients.

Evaluation of the factors influencing brain language laterality in presurgical planning.

PubMed

Batouli, Seyed Amir Hossein; Hasani, Nafiseh; Gheisari, Sara; Behzad, Ebrahim; Oghabian, Mohammad Ali

2016-10-01

Brain lesions cause functional deficits, and one treatment for this condition is lesion resection. In most cases, presurgical planning (PSP) and the information from laterality indices are necessary for maximum preservation of the critical functions after surgery. Language laterality index (LI) is reliably estimated using functional magnetic resonance imaging (fMRI); however, this measure is under the influence of some external factors. In this study, we investigated the influence of a number of factors on language LI, using data from 120 patients (mean age=35.65 (±13.4) years) who underwent fMRI for PSP. Using two proposed language tasks from our previous works, brain left hemisphere was showed to be dominant for the language function, although a higher LI was obtained using the "Word Generation" task, compared to the "Reverse Word Reading". In addition, decline of LIs with age, and lower LI when the lesion invaded brain language area were observed. Meanwhile, gender, lesion side (affected hemisphere), LI calculation strategy, and fMRI analysis Z-values did not statistically show any influences on the LIs. Although fMRI is widely used to estimate language LI, it is shown here that in order to present a reliable language LI and to correctly select the dominant hemisphere of the brain, the influence of external factors should be carefully considered. Copyright © 2016 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Multimodal Classification of Schizophrenia Patients with MEG and fMRI Data Using Static and Dynamic Connectivity Measures

PubMed Central

Cetin, Mustafa S.; Houck, Jon M.; Rashid, Barnaly; Agacoglu, Oktay; Stephen, Julia M.; Sui, Jing; Canive, Jose; Mayer, Andy; Aine, Cheryl; Bustillo, Juan R.; Calhoun, Vince D.

2016-01-01

Mental disorders like schizophrenia are currently diagnosed by physicians/psychiatrists through clinical assessment and their evaluation of patient's self-reported experiences as the illness emerges. There is great interest in identifying biological markers of prognosis at the onset of illness, rather than relying on the evolution of symptoms across time. Functional network connectivity, which indicates a subject's overall level of “synchronicity” of activity between brain regions, demonstrates promise in providing individual subject predictive power. Many previous studies reported functional connectivity changes during resting-state using only functional magnetic resonance imaging (fMRI). Nevertheless, exclusive reliance on fMRI to generate such networks may limit the inference of the underlying dysfunctional connectivity, which is hypothesized to be a factor in patient symptoms, as fMRI measures connectivity via hemodynamics. Therefore, combination of connectivity assessments using fMRI and magnetoencephalography (MEG), which more directly measures neuronal activity, may provide improved classification of schizophrenia than either modality alone. Moreover, recent evidence indicates that metrics of dynamic connectivity may also be critical for understanding pathology in schizophrenia. In this work, we propose a new framework for extraction of important disease related features and classification of patients with schizophrenia based on using both fMRI and MEG to investigate functional network components in the resting state. Results of this study show that the integration of fMRI and MEG provides important information that captures fundamental characteristics of functional network connectivity in schizophrenia and is helpful for prediction of schizophrenia patient group membership. Combined fMRI/MEG methods, using static functional network connectivity analyses, improved classification accuracy relative to use of fMRI or MEG methods alone (by 15 and 12.45%, respectively), while combined fMRI/MEG methods using dynamic functional network connectivity analyses improved classification up to 5.12% relative to use of fMRI alone and up to 17.21% relative to use of MEG alone. PMID:27807403

A brain MRI atlas of the common squirrel monkey, Saimiri sciureus

NASA Astrophysics Data System (ADS)

Gao, Yurui; Schilling, Kurt G.; Khare, Shweta P.; Panda, Swetasudha; Choe, Ann S.; Stepniewska, Iwona; Li, Xia; Ding, Zhoahua; Anderson, Adam; Landman, Bennett A.

2014-03-01

The common squirrel monkey, Saimiri sciureus, is a New World monkey with functional and microstructural organization of central nervous system similar to that of humans. It is one of the most commonly used South American primates in biomedical research. Unlike its Old World macaque cousins, no digital atlases have described the organization of the squirrel monkey brain. Here, we present a multi-modal magnetic resonance imaging (MRI) atlas constructed from the brain of an adult female squirrel monkey. In vivo MRI acquisitions include high resolution T2 structural imaging and low resolution diffusion tensor imaging. Ex vivo MRI acquisitions include high resolution T2 structural imaging and high resolution diffusion tensor imaging. Cortical regions were manually annotated on the co-registered volumes based on published histological sections.

A Hierarchical Model for Simultaneous Detection and Estimation in Multi-subject fMRI Studies

PubMed Central

Degras, David; Lindquist, Martin A.

2014-01-01

In this paper we introduce a new hierarchical model for the simultaneous detection of brain activation and estimation of the shape of the hemodynamic response in multi-subject fMRI studies. The proposed approach circumvents a major stumbling block in standard multi-subject fMRI data analysis, in that it both allows the shape of the hemodynamic response function to vary across region and subjects, while still providing a straightforward way to estimate population-level activation. An e cient estimation algorithm is presented, as is an inferential framework that not only allows for tests of activation, but also for tests for deviations from some canonical shape. The model is validated through simulations and application to a multi-subject fMRI study of thermal pain. PMID:24793829

Efficacy of EMG-triggered electrical arm stimulation in chronic hemiparetic stroke patients.

PubMed

von Lewinski, Friederike; Hofer, Sabine; Kaus, Jürgen; Merboldt, Klaus-Dietmar; Rothkegel, Holger; Schweizer, Renate; Liebetanz, David; Frahm, Jens; Paulus, Walter

2009-01-01

EMG-triggered electrostimulation (EMG-ES) may improve the motor performance of affected limbs of hemiparetic stroke patients even in the chronic stage. This study was designed to characterize cortical activation changes following intensified EMG-ES in chronic stroke patients and to identify predictors for successful rehabilitation depending on disease severity. We studied 9 patients with severe residual hemiparesis, who underwent 8 weeks of daily task-orientated multi-channel EMG-ES of the paretic arm. Before and after treatment, arm function was evaluated clinically and cortical activation patterns were assessed with functional MRI (fMRI) and/or transcranial magnetic stimulation (TMS). As response to therapy, arm function improved in a subset of patients with more capacity in less affected subjects, but there was no significant gain for those with Box & Block test values below 4 at inception. The clinical improvement, if any, was accompanied by an ipsilesional increase in the sensorimotor cortex (SMC) activation area in fMRI and enhanced intracortical facilitation (ICF) as revealed by paired TMS. The SMC activation change in fMRI was predicted by the presence or absence of motor-evoked potentials (MEPs) on the affected side. The present findings support the notion that intensified EMG-ES may improve the arm function in individual chronic hemiparetic stroke patients but not in more severely impaired individuals. Functional improvements are paralleled by increased ipsilesional SMC activation and enhanced ICF supporting neuroplasticity as contributor to rehabilitation. The clinical score at inception and the presence of MEPs have the best predictive potential.

Real-time myocardium segmentation for the assessment of cardiac function variation

NASA Astrophysics Data System (ADS)

Zoehrer, Fabian; Huellebrand, Markus; Chitiboi, Teodora; Oechtering, Thekla; Sieren, Malte; Frahm, Jens; Hahn, Horst K.; Hennemuth, Anja

2017-03-01

Recent developments in MRI enable the acquisition of image sequences with high spatio-temporal resolution. Cardiac motion can be captured without gating and triggering. Image size and contrast relations differ from conventional cardiac MRI cine sequences requiring new adapted analysis methods. We suggest a novel segmentation approach utilizing contrast invariant polar scanning techniques. It has been tested with 20 datasets of arrhythmia patients. The results do not differ significantly more between automatic and manual segmentations than between observers. This indicates that the presented solution could enable clinical applications of real-time MRI for the examination of arrhythmic cardiac motion in the future.

WE-EF-BRD-04: MR in the OR: The Growth and Applications of MRI for Interventional Radiology and Surgery

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

Fahrig, R.

MRI-guided treatment is a growing area of medicine, particularly in radiotherapy and surgery. The exquisite soft tissue anatomic contrast offered by MRI, along with functional imaging, makes the use of MRI during therapeutic procedures very attractive. Challenging the utility of MRI in the therapy room are many issues including the physics of MRI and the impact on the environment and therapeutic instruments, the impact of the room and instruments on the MRI; safety, space, design and cost. In this session, the applications and challenges of MRI-guided treatment will be described. The session format is: Past, present and future: MRI-guided radiotherapymore » from 2005 to 2025: Jan Lagendijk Battling Maxwell’s equations: Physics challenges and solutions for hybrid MRI systems: Paul Keall I want it now!: Advances in MRI acquisition, reconstruction and the use of priors to enable fast anatomic and physiologic imaging to inform guidance and adaptation decisions: Yanle Hu MR in the OR: The growth and applications of MRI for interventional radiology and surgery: Rebecca Fahrig Learning Objectives: To understand the history and trajectory of MRI-guided radiotherapy To understand the challenges of integrating MR imaging systems with linear accelerators To understand the latest in fast MRI methods to enable the visualisation of anatomy and physiology on radiotherapy treatment timescales To understand the growing role and challenges of MRI for image-guided surgical procedures My disclosures are publicly available and updated at: http://sydney.edu.au/medicine/radiation-physics/about-us/disclosures.php.« less

WE-EF-BRD-02: Battling Maxwell’s Equations: Physics Challenges and Solutions for Hybrid MRI Systems

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

Keall, P.

MRI-guided treatment is a growing area of medicine, particularly in radiotherapy and surgery. The exquisite soft tissue anatomic contrast offered by MRI, along with functional imaging, makes the use of MRI during therapeutic procedures very attractive. Challenging the utility of MRI in the therapy room are many issues including the physics of MRI and the impact on the environment and therapeutic instruments, the impact of the room and instruments on the MRI; safety, space, design and cost. In this session, the applications and challenges of MRI-guided treatment will be described. The session format is: Past, present and future: MRI-guided radiotherapymore » from 2005 to 2025: Jan Lagendijk Battling Maxwell’s equations: Physics challenges and solutions for hybrid MRI systems: Paul Keall I want it now!: Advances in MRI acquisition, reconstruction and the use of priors to enable fast anatomic and physiologic imaging to inform guidance and adaptation decisions: Yanle Hu MR in the OR: The growth and applications of MRI for interventional radiology and surgery: Rebecca Fahrig Learning Objectives: To understand the history and trajectory of MRI-guided radiotherapy To understand the challenges of integrating MR imaging systems with linear accelerators To understand the latest in fast MRI methods to enable the visualisation of anatomy and physiology on radiotherapy treatment timescales To understand the growing role and challenges of MRI for image-guided surgical procedures My disclosures are publicly available and updated at: http://sydney.edu.au/medicine/radiation-physics/about-us/disclosures.php.« less

DCE-MRI, DW-MRI, and MRS in Cancer: Challenges and Advantages of Implementing Qualitative and Quantitative Multi-parametric Imaging in the Clinic

PubMed Central

Winfield, Jessica M.; Payne, Geoffrey S.; Weller, Alex; deSouza, Nandita M.

2016-01-01

Abstract Multi-parametric magnetic resonance imaging (mpMRI) offers a unique insight into tumor biology by combining functional MRI techniques that inform on cellularity (diffusion-weighted MRI), vascular properties (dynamic contrast-enhanced MRI), and metabolites (magnetic resonance spectroscopy) and has scope to provide valuable information for prognostication and response assessment. Challenges in the application of mpMRI in the clinic include the technical considerations in acquiring good quality functional MRI data, development of robust techniques for analysis, and clinical interpretation of the results. This article summarizes the technical challenges in acquisition and analysis of multi-parametric MRI data before reviewing the key applications of multi-parametric MRI in clinical research and practice. PMID:27748710

[Functional neuro-navigation and intraoperative magnetic resonance imaging for the resection of gliomas involving eloquent language structures].

PubMed

Chen, Xiao-lei; Xu, Bai-nan; Wang, Fei; Meng, Xiang-hui; Zhang, Jun; Jiang, Jin-li; Yu, Xin-guang; Zhou, Ding-biao

2011-08-01

To explore the clinical value of functional neuro-navigation and high-field-strength intraoperative magnetic resonance imaging (iMRI) for the resection of intracerebral gliomas involving eloquent language structures. From April 2009 to April 2010, 48 patients with intracerebral gliomas involving eloquent language structures, were operated with functional neuro-navigation and iMRI. Blood oxygen level dependent functional MRI (BOLD-fMRI) was used to depict both Broca and Wernicke cortex, while diffusion tensor imaging (DTI) based fiber tracking was used to delineate arcuate fasciculus. The reconstructed language structures were integrated into a navigation system, so that intra-operative microscopic-based functional neuro-navigation could be achieved. iMRI was used to update the images for both language structures and residual tumors. All patients were evaluated for language function pre-operatively and post-operatively upon short-term and long-term follow-up. In all patients, functional neuro-navigation and iMRI were successfully achieved. In 38 cases (79.2%), gross total resection was accomplished, while in the rest 10 cases (20.8%), subtotal resection was achieved. Only 1 case (2.1%) developed long-term (more than 3 months) new language function deficits at post-operative follow-up. No peri-operative mortality was recorded. With functional neuro-navigation and iMRI, the eloquent structures for language can be precisely located, while the resection size can be accurately evaluated intra-operatively. This technique is safe and helpful for preservation of language function.

PET/MRI assessment of the infarcted mouse heart

NASA Astrophysics Data System (ADS)

Buonincontri, Guido; Methner, Carmen; Krieg, Thomas; Hawkes, Robert C.; Adrian Carpenter, T.; Sawiak, Stephen J.

2014-01-01

Heart failure originating from myocardial infarction (MI) is a leading cause of death worldwide. Mouse models of ischaemia and reperfusion injury (I/R) are used to study the effects of novel treatment strategies targeting MI, however staging disease and treatment efficacy is a challenge. Damage and recovery can be assessed on the cellular, tissue or whole-organ scale but these are rarely measured in concert. Here, for the first time, we present data showing measures of injury in infarcted mice using complementary techniques for multi-modal characterisation of the heart. We use in vivo magnetic resonance imaging (MRI) to assess heart function with cine-MRI, hindered perfusion with late gadolinium enhancement imaging and muscular function with displacement encoded with stimulated echoes (DENSE) MRI. These measures are followed by positron emission tomography (PET) with 18-F-fluorodeoxyglucose to assess cellular metabolism. We demonstrate a protocol combining each of these measures for the same animal in the same imaging session and compare how the different markers can be used to quantify cardiac recovery on different scales following injury.

Automatic selection of arterial input function using tri-exponential models

NASA Astrophysics Data System (ADS)

Yao, Jianhua; Chen, Jeremy; Castro, Marcelo; Thomasson, David

2009-02-01

Dynamic Contrast Enhanced MRI (DCE-MRI) is one method for drug and tumor assessment. Selecting a consistent arterial input function (AIF) is necessary to calculate tissue and tumor pharmacokinetic parameters in DCE-MRI. This paper presents an automatic and robust method to select the AIF. The first stage is artery detection and segmentation, where knowledge about artery structure and dynamic signal intensity temporal properties of DCE-MRI is employed. The second stage is AIF model fitting and selection. A tri-exponential model is fitted for every candidate AIF using the Levenberg-Marquardt method, and the best fitted AIF is selected. Our method has been applied in DCE-MRIs of four different body parts: breast, brain, liver and prostate. The success rates in artery segmentation for 19 cases are 89.6%+/-15.9%. The pharmacokinetic parameters computed from the automatically selected AIFs are highly correlated with those from manually determined AIFs (R2=0.946, P(T<=t)=0.09). Our imaging-based tri-exponential AIF model demonstrated significant improvement over a previously proposed bi-exponential model.

Brain activation patterns elicited by the 'Faces Symbol Test' -- a pilot fMRI study.

PubMed

Grabner, Rh; Popotnig, F; Ropele, S; Neuper, C; Gorani, F; Petrovic, K; Ebner, F; Strasser-Fuchs, S; Fazekas, F; Enzinger, C

2008-04-01

The Faces Symbol Test (FST) has recently been proposed as a brief and patient-friendly screening instrument for the assessment of cognitive dysfunction in patients with multiple sclerosis (MS). However, in contrast to well-established MS screening tests such as the Paced Auditory Serial Addition Test, the neural correlates of the FST have not been investigated so far. In the present study, we developed a functional MRI (fMRI) version of the FST to provide first data on brain regions and networks involved in this test. A sample of 19 healthy participants completed a version of the FST adapted for fMRI, requiring matching of faces and symbols in a multiple choice test and two further experimental conditions drawing on cognitive subcomponents (face matching and symbol matching). Imaging data showed a differential involvement of a fronto-parieto-occipital network in the three conditions. The most demanding FST condition elicited brain activation patterns related with sustained attention and executive control. These results suggest that the FST recruits brain networks critical for higher-order cognitive functions often impaired in MS patients.

Brain functional BOLD perturbation modelling for forward fMRI and inverse mapping

PubMed Central

Robinson, Jennifer; Calhoun, Vince

2018-01-01

Purpose To computationally separate dynamic brain functional BOLD responses from static background in a brain functional activity for forward fMRI signal analysis and inverse mapping. Methods A brain functional activity is represented in terms of magnetic source by a perturbation model: χ = χ0 +δχ, with δχ for BOLD magnetic perturbations and χ0 for background. A brain fMRI experiment produces a timeseries of complex-valued images (T2* images), whereby we extract the BOLD phase signals (denoted by δP) by a complex division. By solving an inverse problem, we reconstruct the BOLD δχ dataset from the δP dataset, and the brain χ distribution from a (unwrapped) T2* phase image. Given a 4D dataset of task BOLD fMRI, we implement brain functional mapping by temporal correlation analysis. Results Through a high-field (7T) and high-resolution (0.5mm in plane) task fMRI experiment, we demonstrated in detail the BOLD perturbation model for fMRI phase signal separation (P + δP) and reconstructing intrinsic brain magnetic source (χ and δχ). We also provided to a low-field (3T) and low-resolution (2mm) task fMRI experiment in support of single-subject fMRI study. Our experiments show that the δχ-depicted functional map reveals bidirectional BOLD χ perturbations during the task performance. Conclusions The BOLD perturbation model allows us to separate fMRI phase signal (by complex division) and to perform inverse mapping for pure BOLD δχ reconstruction for intrinsic functional χ mapping. The full brain χ reconstruction (from unwrapped fMRI phase) provides a new brain tissue image that allows to scrutinize the brain tissue idiosyncrasy for the pure BOLD δχ response through an automatic function/structure co-localization. PMID:29351339

Validity of semi-quantitative scale for brain MRI in unilateral cerebral palsy due to periventricular white matter lesions: Relationship with hand sensorimotor function and structural connectivity

PubMed Central

Fiori, Simona; Guzzetta, Andrea; Pannek, Kerstin; Ware, Robert S.; Rossi, Giuseppe; Klingels, Katrijn; Feys, Hilde; Coulthard, Alan; Cioni, Giovanni; Rose, Stephen; Boyd, Roslyn N.

2015-01-01

Aim To provide first evidence of construct validity of a semi-quantitative scale for brain structural MRI (sqMRI scale) in children with unilateral cerebral palsy (UCP) secondary to periventricular white matter (PWM) lesions, by examining the relationship with hand sensorimotor function and whole brain structural connectivity. Methods Cross-sectional study of 50 children with UCP due to PWM lesions using 3 T (MRI), diffusion MRI and assessment of hand sensorimotor function. We explored the relationship of lobar, hemispheric and global scores on the sqMRI scale, with fractional anisotropy (FA), as a measure of brain white matter microstructure, and with hand sensorimotor measures (Assisting Hand Assessment, AHA; Jebsen–Taylor Test for Hand Function, JTTHF; Melbourne Assessment of Unilateral Upper Limb Function, MUUL; stereognosis; 2-point discrimination). Results Lobar and hemispheric scores on the sqMRI scale contralateral to the clinical side of hemiplegia correlated with sensorimotor paretic hand function measures and FA of a number of brain structural connections, including connections of brain areas involved in motor control (postcentral, precentral and paracentral gyri in the parietal lobe). More severe lesions correlated with lower sensorimotor performance, with the posterior limb of internal capsule score being the strongest contributor to impaired hand function. Conclusion The sqMRI scale demonstrates first evidence of construct validity against impaired motor and sensory function measures and brain structural connectivity in a cohort of children with UCP due to PWM lesions. More severe lesions correlated with poorer paretic hand sensorimotor function and impaired structural connectivity in the hemisphere contralateral to the clinical side of hemiplegia. The quantitative structural MRI scoring may be a useful clinical tool for studying brain structure–function relationships but requires further validation in other populations of CP. PMID:26106533

A Magnetic Resonance Compatible Soft Wearable Robotic Glove for Hand Rehabilitation and Brain Imaging.

PubMed

Hong Kai Yap; Kamaldin, Nazir; Jeong Hoon Lim; Nasrallah, Fatima A; Goh, James Cho Hong; Chen-Hua Yeow

2017-06-01

In this paper, we present the design, fabrication and evaluation of a soft wearable robotic glove, which can be used with functional Magnetic Resonance imaging (fMRI) during the hand rehabilitation and task specific training. The soft wearable robotic glove, called MR-Glove, consists of two major components: a) a set of soft pneumatic actuators and b) a glove. The soft pneumatic actuators, which are made of silicone elastomers, generate bending motion and actuate finger joints upon pressurization. The device is MR-compatible as it contains no ferromagnetic materials and operates pneumatically. Our results show that the device did not cause artifacts to fMRI images during hand rehabilitation and task-specific exercises. This study demonstrated the possibility of using fMRI and MR-compatible soft wearable robotic device to study brain activities and motor performances during hand rehabilitation, and to unravel the functional effects of rehabilitation robotics on brain stimulation.

A Simple fMRI Compatible Robotic Stimulator to Study the Neural Mechanisms of Touch and Pain.

PubMed

Riillo, F; Bagnato, C; Allievi, A G; Takagi, A; Fabrizi, L; Saggio, G; Arichi, T; Burdet, E

2016-08-01

This paper presents a simple device for the investigation of the human somatosensory system with functional magnetic imaging (fMRI). PC-controlled pneumatic actuation is employed to produce innocuous or noxious mechanical stimulation of the skin. Stimulation patterns are synchronized with fMRI and other relevant physiological measurements like electroencephalographic activity and vital physiological parameters. The system allows adjustable regulation of stimulation parameters and provides consistent patterns of stimulation. A validation experiment demonstrates that the system safely and reliably identifies clusters of functional activity in brain regions involved in the processing of pain. This new device is inexpensive, portable, easy-to-assemble and customizable to suit different experimental requirements. It provides robust and consistent somatosensory stimulation, which is of crucial importance to investigating the mechanisms of pain and its strong connection with the sense of touch.

Non-parametric representation and prediction of single- and multi-shell diffusion-weighted MRI data using Gaussian processes

PubMed Central

Andersson, Jesper L.R.; Sotiropoulos, Stamatios N.

2015-01-01

Diffusion MRI offers great potential in studying the human brain microstructure and connectivity. However, diffusion images are marred by technical problems, such as image distortions and spurious signal loss. Correcting for these problems is non-trivial and relies on having a mechanism that predicts what to expect. In this paper we describe a novel way to represent and make predictions about diffusion MRI data. It is based on a Gaussian process on one or several spheres similar to the Geostatistical method of “Kriging”. We present a choice of covariance function that allows us to accurately predict the signal even from voxels with complex fibre patterns. For multi-shell data (multiple non-zero b-values) the covariance function extends across the shells which means that data from one shell is used when making predictions for another shell. PMID:26236030

Reward Prediction Errors in Drug Addiction and Parkinson's Disease: from Neurophysiology to Neuroimaging.

PubMed

García-García, Isabel; Zeighami, Yashar; Dagher, Alain

2017-06-01

Surprises are important sources of learning. Cognitive scientists often refer to surprises as "reward prediction errors," a parameter that captures discrepancies between expectations and actual outcomes. Here, we integrate neurophysiological and functional magnetic resonance imaging (fMRI) results addressing the processing of reward prediction errors and how they might be altered in drug addiction and Parkinson's disease. By increasing phasic dopamine responses, drugs might accentuate prediction error signals, causing increases in fMRI activity in mesolimbic areas in response to drugs. Chronic substance dependence, by contrast, has been linked with compromised dopaminergic function, which might be associated with blunted fMRI responses to pleasant non-drug stimuli in mesocorticolimbic areas. In Parkinson's disease, dopamine replacement therapies seem to induce impairments in learning from negative outcomes. The present review provides a holistic overview of reward prediction errors across different pathologies and might inform future clinical strategies targeting impulsive/compulsive disorders.

MRI-conditional pacemakers: current perspectives.

PubMed

Ferreira, António M; Costa, Francisco; Tralhão, António; Marques, Hugo; Cardim, Nuno; Adragão, Pedro

2014-01-01

Use of both magnetic resonance imaging (MRI) and pacing devices has undergone remarkable growth in recent years, and it is estimated that the majority of patients with pacemakers will need an MRI during their lifetime. These investigations will generally be denied due to the potentially dangerous interactions between cardiac devices and the magnetic fields and radio frequency energy used in MRI. Despite the increasing reports of uneventful scanning in selected patients with conventional pacemakers under close surveillance, MRI is still contraindicated in those circumstances and cannot be considered a routine procedure. These limitations prompted a series of modifications in generator and lead engineering, designed to minimize interactions that could compromise device function and patient safety. The resulting MRI-conditional pacemakers were first introduced in 2008 and the clinical experience gathered so far supports their safety in the MRI environment if certain conditions are fulfilled. With this technology, new questions and controversies arise regarding patient selection, clinical impact, and cost-effectiveness. In this review, we discuss the potential risks of MRI in patients with electronic cardiac devices and present updated information regarding the features of MRI-conditional pacemakers and the clinical experience with currently available models. Finally, we provide some guidance on how to scan patients who have these devices and discuss future directions in the field.

Automated segmentation and reconstruction of patient-specific cardiac anatomy and pathology from in vivo MRI*

NASA Astrophysics Data System (ADS)

Ringenberg, Jordan; Deo, Makarand; Devabhaktuni, Vijay; Filgueiras-Rama, David; Pizarro, Gonzalo; Ibañez, Borja; Berenfeld, Omer; Boyers, Pamela; Gold, Jeffrey

2012-12-01

This paper presents an automated method to segment left ventricle (LV) tissues from functional and delayed-enhancement (DE) cardiac magnetic resonance imaging (MRI) scans using a sequential multi-step approach. First, a region of interest (ROI) is computed to create a subvolume around the LV using morphological operations and image arithmetic. From the subvolume, the myocardial contours are automatically delineated using difference of Gaussians (DoG) filters and GSV snakes. These contours are used as a mask to identify pathological tissues, such as fibrosis or scar, within the DE-MRI. The presented automated technique is able to accurately delineate the myocardium and identify the pathological tissue in patient sets. The results were validated by two expert cardiologists, and in one set the automated results are quantitatively and qualitatively compared with expert manual delineation. Furthermore, the method is patient-specific, performed on an entire patient MRI series. Thus, in addition to providing a quick analysis of individual MRI scans, the fully automated segmentation method is used for effectively tagging regions in order to reconstruct computerized patient-specific 3D cardiac models. These models can then be used in electrophysiological studies and surgical strategy planning.

Functional Magnetic Resonance Imaging (MRI) and MRI Tractography in Progressive Supranuclear Palsy-Like Syndrome

PubMed Central

Vaphiades, Michael S.; Visscher, Kristina; Rucker, Janet C.; Vattoth, Surjith; Roberson, Glenn H.

2015-01-01

ABSTRACT An 18-year-old woman underwent an uneventful ascending aortic aneurysm repair then developed progressive supranuclear palsy-like syndrome. Extensive neuroimaging including contrasted fat-suppressed cranial and orbital magnetic resonance imaging (MRI), MRI tractography, and functional MRI (fMRI) revealed no clear radiographic involvement except for a single tiny hypoechoic midbrain dot on the T2*-weighted gradient-echo imaging, which is not considered sufficient to account for the patient’s deficits. This case attests to the occult nature of this rare and devastating syndrome. PMID:27928334

PyMVPA: A python toolbox for multivariate pattern analysis of fMRI data.

PubMed

Hanke, Michael; Halchenko, Yaroslav O; Sederberg, Per B; Hanson, Stephen José; Haxby, James V; Pollmann, Stefan

2009-01-01

Decoding patterns of neural activity onto cognitive states is one of the central goals of functional brain imaging. Standard univariate fMRI analysis methods, which correlate cognitive and perceptual function with the blood oxygenation-level dependent (BOLD) signal, have proven successful in identifying anatomical regions based on signal increases during cognitive and perceptual tasks. Recently, researchers have begun to explore new multivariate techniques that have proven to be more flexible, more reliable, and more sensitive than standard univariate analysis. Drawing on the field of statistical learning theory, these new classifier-based analysis techniques possess explanatory power that could provide new insights into the functional properties of the brain. However, unlike the wealth of software packages for univariate analyses, there are few packages that facilitate multivariate pattern classification analyses of fMRI data. Here we introduce a Python-based, cross-platform, and open-source software toolbox, called PyMVPA, for the application of classifier-based analysis techniques to fMRI datasets. PyMVPA makes use of Python's ability to access libraries written in a large variety of programming languages and computing environments to interface with the wealth of existing machine learning packages. We present the framework in this paper and provide illustrative examples on its usage, features, and programmability.

PyMVPA: A Python toolbox for multivariate pattern analysis of fMRI data

PubMed Central

Hanke, Michael; Halchenko, Yaroslav O.; Sederberg, Per B.; Hanson, Stephen José; Haxby, James V.; Pollmann, Stefan

2009-01-01

Decoding patterns of neural activity onto cognitive states is one of the central goals of functional brain imaging. Standard univariate fMRI analysis methods, which correlate cognitive and perceptual function with the blood oxygenation-level dependent (BOLD) signal, have proven successful in identifying anatomical regions based on signal increases during cognitive and perceptual tasks. Recently, researchers have begun to explore new multivariate techniques that have proven to be more flexible, more reliable, and more sensitive than standard univariate analysis. Drawing on the field of statistical learning theory, these new classifier-based analysis techniques possess explanatory power that could provide new insights into the functional properties of the brain. However, unlike the wealth of software packages for univariate analyses, there are few packages that facilitate multivariate pattern classification analyses of fMRI data. Here we introduce a Python-based, cross-platform, and open-source software toolbox, called PyMVPA, for the application of classifier-based analysis techniques to fMRI datasets. PyMVPA makes use of Python's ability to access libraries written in a large variety of programming languages and computing environments to interface with the wealth of existing machine-learning packages. We present the framework in this paper and provide illustrative examples on its usage, features, and programmability. PMID:19184561

Functional Brain Activation Differences in Stuttering Identified with a Rapid fMRI Sequence

ERIC Educational Resources Information Center

Loucks, Torrey; Kraft, Shelly Jo; Choo, Ai Leen; Sharma, Harish; Ambrose, Nicoline G.

2011-01-01

The purpose of this study was to investigate whether brain activity related to the presence of stuttering can be identified with rapid functional MRI (fMRI) sequences that involved overt and covert speech processing tasks. The long-term goal is to develop sensitive fMRI approaches with developmentally appropriate tasks to identify deviant speech…

Distinct and overlapping fMRI activation networks for processing of novel identities and locations of objects.

PubMed

Pihlajamäki, Maija; Tanila, Heikki; Könönen, Mervi; Hänninen, Tuomo; Aronen, Hannu J; Soininen, Hilkka

2005-10-01

The ventral visual stream processes information about the identity of objects ('what'), whereas the dorsal stream processes the spatial locations of objects ('where'). There is a corresponding, although disputed, distinction for the ventrolateral and dorsolateral prefrontal areas. Furthermore, there seems to be a distinction between the anterior and posterior medial temporal lobe (MTL) structures in the processing of novel items and new spatial arrangements, respectively. Functional differentiation of the intermediary mid-line cortical and temporal neocortical structures that communicate with the occipitotemporal, occipitoparietal, prefrontal, and MTL structures, however, is unclear. Therefore, in the present functional magnetic resonance imaging (fMRI) study, we examined whether the distinction among the MTL structures extends to these closely connected cortical areas. The most striking difference in the fMRI responses during visual presentation of changes in either items or their locations was the bilateral activation of the temporal lobe and ventrolateral prefrontal cortical areas for novel object identification in contrast to wide parietal and dorsolateral prefrontal activation for the novel locations of objects. An anterior-posterior distinction of fMRI responses similar to the MTL was observed in the cingulate/retrosplenial, and superior and middle temporal cortices. In addition to the distinct areas of activation, certain frontal, parietal, and temporo-occipital areas responded to both object and spatial novelty, suggesting a common attentional network for both types of changes in the visual environment. These findings offer new insights to the functional roles and intrinsic specialization of the cingulate/retrosplenial, and lateral temporal cortical areas in visuospatial cognition.

Haemodynamic imaging of thoracic stent-grafts by computational fluid dynamics (CFD): presentation of a patient-specific method combining magnetic resonance imaging and numerical simulations.

PubMed

Midulla, Marco; Moreno, Ramiro; Baali, Adil; Chau, Ming; Negre-Salvayre, Anne; Nicoud, Franck; Pruvo, Jean-Pierre; Haulon, Stephan; Rousseau, Hervé

2012-10-01

In the last decade, there was been increasing interest in finding imaging techniques able to provide a functional vascular imaging of the thoracic aorta. The purpose of this paper is to present an imaging method combining magnetic resonance imaging (MRI) and computational fluid dynamics (CFD) to obtain a patient-specific haemodynamic analysis of patients treated by thoracic endovascular aortic repair (TEVAR). MRI was used to obtain boundary conditions. MR angiography (MRA) was followed by cardiac-gated cine sequences which covered the whole thoracic aorta. Phase contrast imaging provided the inlet and outlet profiles. A CFD mesh generator was used to model the arterial morphology, and wall movements were imposed according to the cine imaging. CFD runs were processed using the finite volume (FV) method assuming blood as a homogeneous Newtonian fluid. Twenty patients (14 men; mean age 62.2 years) with different aortic lesions were evaluated. Four-dimensional mapping of velocity and wall shear stress were obtained, depicting different patterns of flow (laminar, turbulent, stenosis-like) and local alterations of parietal stress in-stent and along the native aorta. A computational method using a combined approach with MRI appears feasible and seems promising to provide detailed functional analysis of thoracic aorta after stent-graft implantation. • Functional vascular imaging of the thoracic aorta offers new diagnostic opportunities • CFD can model vascular haemodynamics for clinical aortic problems • Combining CFD with MRI offers patient specific method of aortic analysis • Haemodynamic analysis of stent-grafts could improve clinical management and follow-up.

The Cognitive Neuroscience of Sign Language: Engaging Undergraduate Students' Critical Thinking Skills Using the Primary Literature.

PubMed

Stevens, Courtney

2015-01-01

This article presents a modular activity on the neurobiology of sign language that engages undergraduate students in reading and analyzing the primary functional magnetic resonance imaging (fMRI) literature. Drawing on a seed empirical article and subsequently published critique and rebuttal, students are introduced to a scientific debate concerning the functional significance of right-hemisphere recruitment observed in some fMRI studies of sign language processing. The activity requires minimal background knowledge and is not designed to provide students with a specific conclusion regarding the debate. Instead, the activity and set of articles allow students to consider key issues in experimental design and analysis of the primary literature, including critical thinking regarding the cognitive subtractions used in blocked-design fMRI studies, as well as possible confounds in comparing results across different experimental tasks. By presenting articles representing different perspectives, each cogently argued by leading scientists, the readings and activity also model the type of debate and dialogue critical to science, but often invisible to undergraduate science students. Student self-report data indicate that undergraduates find the readings interesting and that the activity enhances their ability to read and interpret primary fMRI articles, including evaluating research design and considering alternate explanations of study results. As a stand-alone activity completed primarily in one 60-minute class block, the activity can be easily incorporated into existing courses, providing students with an introduction both to the analysis of empirical fMRI articles and to the role of debate and critique in the field of neuroscience.

Effects of haloperidol and aripiprazole on the human mesolimbic motivational system: A pharmacological fMRI study.

PubMed

Bolstad, Ingeborg; Andreassen, Ole A; Groote, Inge; Server, Andres; Sjaastad, Ivar; Kapur, Shitij; Jensen, Jimmy

2015-12-01

The atypical antipsychotic drug aripiprazole is a partial dopamine (DA) D2 receptor agonist, which differentiates it from most other antipsychotics. This study compares the brain activation characteristic produced by aripiprazole with that of haloperidol, a typical D2 receptor antagonist. Healthy participants received an acute oral dose of haloperidol, aripiprazole or placebo, and then performed an active aversive conditioning task with aversive and neutral events presented as sounds, while blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) was carried out. The fMRI task, targeting the mesolimbic motivational system that is thought to be disturbed in psychosis, was based on the conditioned avoidance response (CAR) animal model - a widely used test of therapeutic potential of antipsychotic drugs. In line with the CAR animal model, the present results show that subjects given haloperidol were not able to avoid more aversive than neutral task trials, even though the response times were shorter during aversive events. In the aripiprazole and placebo groups more aversive than neutral events were avoided. Accordingly, the task-related BOLD-fMRI response in the mesolimbic motivational system was diminished in the haloperidol group compared to the placebo group, particularly in the ventral striatum, whereas the aripiprazole group showed task-related activations intermediate of the placebo and haloperidol groups. The current results show differential effects on brain function by aripiprazole and haloperidol, probably related to altered DA transmission. This supports the use of pharmacological fMRI to study antipsychotic properties in humans. Copyright © 2015 Elsevier B.V. and ECNP. All rights reserved.

The Cognitive Neuroscience of Sign Language: Engaging Undergraduate Students’ Critical Thinking Skills Using the Primary Literature

PubMed Central

Stevens, Courtney

2015-01-01

This article presents a modular activity on the neurobiology of sign language that engages undergraduate students in reading and analyzing the primary functional magnetic resonance imaging (fMRI) literature. Drawing on a seed empirical article and subsequently published critique and rebuttal, students are introduced to a scientific debate concerning the functional significance of right-hemisphere recruitment observed in some fMRI studies of sign language processing. The activity requires minimal background knowledge and is not designed to provide students with a specific conclusion regarding the debate. Instead, the activity and set of articles allow students to consider key issues in experimental design and analysis of the primary literature, including critical thinking regarding the cognitive subtractions used in blocked-design fMRI studies, as well as possible confounds in comparing results across different experimental tasks. By presenting articles representing different perspectives, each cogently argued by leading scientists, the readings and activity also model the type of debate and dialogue critical to science, but often invisible to undergraduate science students. Student self-report data indicate that undergraduates find the readings interesting and that the activity enhances their ability to read and interpret primary fMRI articles, including evaluating research design and considering alternate explanations of study results. As a stand-alone activity completed primarily in one 60-minute class block, the activity can be easily incorporated into existing courses, providing students with an introduction both to the analysis of empirical fMRI articles and to the role of debate and critique in the field of neuroscience. PMID:26557797

One dimensional spatial resolution optimization on a hybrid low field MRI-gamma detector

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

Agulles-Pedrós, L., E-mail: lagullesp@unal.edu.co; Abril, A., E-mail: ajabrilf@unal.edu.co

Hybrid systems like Positron Emission Tomography/Magnetic Resonance Imaging (PET/MRI) and MRI/gamma camera, offer advantages combining the resolution and contrast capability of MRI with the better contrast and functional information of nuclear medicine techniques. However, the radiation detectors are expensive and need an electronic set-up, which can interfere with the MRI acquisition process or viceversa. In order to improve these drawbacks, in this work it is presented the design of a low field NMR system made up of permanent magnets compatible with a gamma radiation detector based on gel dosimetry. The design is performed using the software FEMM for estimation ofmore » the magnetic field, and GEANT4 for the physical process involved in radiation detection and effect of magnetic field. The homogeneity in magnetic field is achieved with an array of NbFeB magnets in a linear configuration with a separation between the magnets, minimizing the effect of Compton back scattering compared with a no-spacing linear configuration. The final magnetic field in the homogeneous zone is ca. 100 mT. In this hybrid proposal, although the gel detector do not have spatial resolution per se, it is possible to obtain a dose profile (1D image) as a function of the position by using a collimator array. As a result, the gamma detector system described allows a complete integrated radiation detector within the low field NMR (lfNMR) system. Finally we present the better configuration for the hybrid system considering the collimator parameters such as height, thickness and distance.« less

Methodological challenges and solutions in auditory functional magnetic resonance imaging

PubMed Central

Peelle, Jonathan E.

2014-01-01

Functional magnetic resonance imaging (fMRI) studies involve substantial acoustic noise. This review covers the difficulties posed by such noise for auditory neuroscience, as well as a number of possible solutions that have emerged. Acoustic noise can affect the processing of auditory stimuli by making them inaudible or unintelligible, and can result in reduced sensitivity to auditory activation in auditory cortex. Equally importantly, acoustic noise may also lead to increased listening effort, meaning that even when auditory stimuli are perceived, neural processing may differ from when the same stimuli are presented in quiet. These and other challenges have motivated a number of approaches for collecting auditory fMRI data. Although using a continuous echoplanar imaging (EPI) sequence provides high quality imaging data, these data may also be contaminated by background acoustic noise. Traditional sparse imaging has the advantage of avoiding acoustic noise during stimulus presentation, but at a cost of reduced temporal resolution. Recently, three classes of techniques have been developed to circumvent these limitations. The first is Interleaved Silent Steady State (ISSS) imaging, a variation of sparse imaging that involves collecting multiple volumes following a silent period while maintaining steady-state longitudinal magnetization. The second involves active noise control to limit the impact of acoustic scanner noise. Finally, novel MRI sequences that reduce the amount of acoustic noise produced during fMRI make the use of continuous scanning a more practical option. Together these advances provide unprecedented opportunities for researchers to collect high-quality data of hemodynamic responses to auditory stimuli using fMRI. PMID:25191218

Altered resting-state whole-brain functional networks of neonates with intrauterine growth restriction.

PubMed

Batalle, Dafnis; Muñoz-Moreno, Emma; Tornador, Cristian; Bargallo, Nuria; Deco, Gustavo; Eixarch, Elisenda; Gratacos, Eduard

2016-04-01

The feasibility to use functional MRI (fMRI) during natural sleep to assess low-frequency basal brain activity fluctuations in human neonates has been demonstrated, although its potential to characterise pathologies of prenatal origin has not yet been exploited. In the present study, we used intrauterine growth restriction (IUGR) as a model of altered neurodevelopment due to prenatal condition to show the suitability of brain networks to characterise functional brain organisation at neonatal age. Particularly, we analysed resting-state fMRI signal of 20 neonates with IUGR and 13 controls, obtaining whole-brain functional networks based on correlations of blood oxygen level-dependent (BOLD) signal in 90 grey matter regions of an anatomical atlas (AAL). Characterisation of the networks obtained with graph theoretical features showed increased network infrastructure and raw efficiencies but reduced efficiency after normalisation, demonstrating hyper-connected but sub-optimally organised IUGR functional brain networks. Significant association of network features with neurobehavioral scores was also found. Further assessment of spatiotemporal dynamics displayed alterations into features associated to frontal, cingulate and lingual cortices. These findings show the capacity of functional brain networks to characterise brain reorganisation from an early age, and their potential to develop biomarkers of altered neurodevelopment. Copyright © 2016 Elsevier Ltd. All rights reserved.

Broadband Electrophysiological Dynamics Contribute to Global Resting-State fMRI Signal.

PubMed

Wen, Haiguang; Liu, Zhongming

2016-06-01

Spontaneous activity observed with resting-state fMRI is used widely to uncover the brain's intrinsic functional networks in health and disease. Although many networks appear modular and specific, global and nonspecific fMRI fluctuations also exist and both pose a challenge and present an opportunity for characterizing and understanding brain networks. Here, we used a multimodal approach to investigate the neural correlates to the global fMRI signal in the resting state. Like fMRI, resting-state power fluctuations of broadband and arrhythmic, or scale-free, macaque electrocorticography and human magnetoencephalography activity were correlated globally. The power fluctuations of scale-free human electroencephalography (EEG) were coupled with the global component of simultaneously acquired resting-state fMRI, with the global hemodynamic change lagging the broadband spectral change of EEG by ∼5 s. The levels of global and nonspecific fluctuation and synchronization in scale-free population activity also varied across and depended on arousal states. Together, these results suggest that the neural origin of global resting-state fMRI activity is the broadband power fluctuation in scale-free population activity observable with macroscopic electrical or magnetic recordings. Moreover, the global fluctuation in neurophysiological and hemodynamic activity is likely modulated through diffuse neuromodulation pathways that govern arousal states and vigilance levels. This study provides new insights into the neural origin of resting-state fMRI. Results demonstrate that the broadband power fluctuation of scale-free electrophysiology is globally synchronized and directly coupled with the global component of spontaneous fMRI signals, in contrast to modularly synchronized fluctuations in oscillatory neural activity. These findings lead to a new hypothesis that scale-free and oscillatory neural processes account for global and modular patterns of functional connectivity observed with resting-state fMRI, respectively. Copyright © 2016 the authors 0270-6474/16/366030-11$15.00/0.

Real-Time Functional Magnetic Resonance Imaging Amygdala Neurofeedback Changes Positive Information Processing in Major Depressive Disorder.

PubMed

Young, Kymberly D; Misaki, Masaya; Harmer, Catherine J; Victor, Teresa; Zotev, Vadim; Phillips, Raquel; Siegle, Greg J; Drevets, Wayne C; Bodurka, Jerzy

2017-10-15

In participants with major depressive disorder who are trained to upregulate their amygdalar hemodynamic responses during positive autobiographical memory recall with real-time functional magnetic resonance imaging neurofeedback (rtfMRI-nf) training, depressive symptoms diminish. This study tested whether amygdalar rtfMRI-nf also changes emotional processing of positive and negative stimuli in a variety of behavioral and imaging tasks. Patients with major depressive disorder completed two rtfMRI-nf sessions (18 received amygdalar rtfMRI-nf, 16 received control parietal rtfMRI-nf). One week before and following rtfMRI-nf training, participants performed tasks measuring responses to emotionally valenced stimuli including a backward-masking task, which measures the amygdalar hemodynamic response to emotional faces presented for traditionally subliminal duration and followed by a mask, and the Emotional Test Battery in which reaction times and performance accuracy are measured during tasks involving emotional faces and words. During the backward-masking task, amygdalar responses increased while viewing masked happy faces but decreased to masked sad faces in the experimental versus control group following rtfMRI-nf. During the Emotional Test Battery, reaction times decreased to identification of positive faces and during self-identification with positive words and vigilance scores increased to positive faces and decreased to negative faces during the faces dot-probe task in the experimental versus control group following rtfMRI-nf. rtfMRI-nf training to increase the amygdalar hemodynamic response to positive memories was associated with changes in amygdalar responses to happy and sad faces and improved processing of positive stimuli during performance of the Emotional Test Battery. These results may suggest that amygdalar rtfMRI-nf training alters responses to emotional stimuli in a manner similar to antidepressant pharmacotherapy. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Linear Discriminant Analysis Achieves High Classification Accuracy for the BOLD fMRI Response to Naturalistic Movie Stimuli

PubMed Central

Mandelkow, Hendrik; de Zwart, Jacco A.; Duyn, Jeff H.

2016-01-01

Naturalistic stimuli like movies evoke complex perceptual processes, which are of great interest in the study of human cognition by functional MRI (fMRI). However, conventional fMRI analysis based on statistical parametric mapping (SPM) and the general linear model (GLM) is hampered by a lack of accurate parametric models of the BOLD response to complex stimuli. In this situation, statistical machine-learning methods, a.k.a. multivariate pattern analysis (MVPA), have received growing attention for their ability to generate stimulus response models in a data-driven fashion. However, machine-learning methods typically require large amounts of training data as well as computational resources. In the past, this has largely limited their application to fMRI experiments involving small sets of stimulus categories and small regions of interest in the brain. By contrast, the present study compares several classification algorithms known as Nearest Neighbor (NN), Gaussian Naïve Bayes (GNB), and (regularized) Linear Discriminant Analysis (LDA) in terms of their classification accuracy in discriminating the global fMRI response patterns evoked by a large number of naturalistic visual stimuli presented as a movie. Results show that LDA regularized by principal component analysis (PCA) achieved high classification accuracies, above 90% on average for single fMRI volumes acquired 2 s apart during a 300 s movie (chance level 0.7% = 2 s/300 s). The largest source of classification errors were autocorrelations in the BOLD signal compounded by the similarity of consecutive stimuli. All classifiers performed best when given input features from a large region of interest comprising around 25% of the voxels that responded significantly to the visual stimulus. Consistent with this, the most informative principal components represented widespread distributions of co-activated brain regions that were similar between subjects and may represent functional networks. In light of these results, the combination of naturalistic movie stimuli and classification analysis in fMRI experiments may prove to be a sensitive tool for the assessment of changes in natural cognitive processes under experimental manipulation. PMID:27065832

Reproducibility and Temporal Structure in Weekly Resting-State fMRI over a Period of 3.5 Years

PubMed Central

Choe, Ann S.; Jones, Craig K.; Joel, Suresh E.; Muschelli, John; Belegu, Visar; Caffo, Brian S.; Lindquist, Martin A.; van Zijl, Peter C. M.; Pekar, James J.

2015-01-01

Resting-state functional MRI (rs-fMRI) permits study of the brain’s functional networks without requiring participants to perform tasks. Robust changes in such resting state networks (RSNs) have been observed in neurologic disorders, and rs-fMRI outcome measures are candidate biomarkers for monitoring clinical trials, including trials of extended therapeutic interventions for rehabilitation of patients with chronic conditions. In this study, we aim to present a unique longitudinal dataset reporting on a healthy adult subject scanned weekly over 3.5 years and identify rs-fMRI outcome measures appropriate for clinical trials. Accordingly, we assessed the reproducibility, and characterized the temporal structure of, rs-fMRI outcome measures derived using independent component analysis (ICA). Data was compared to a 21-person dataset acquired on the same scanner in order to confirm that the values of the single-subject RSN measures were within the expected range as assessed from the multi-participant dataset. Fourteen RSNs were identified, and the inter-session reproducibility of outcome measures—network spatial map, temporal signal fluctuation magnitude, and between-network connectivity (BNC)–was high, with executive RSNs showing the highest reproducibility. Analysis of the weekly outcome measures also showed that many rs-fMRI outcome measures had a significant linear trend, annual periodicity, and persistence. Such temporal structure was most prominent in spatial map similarity, and least prominent in BNC. High reproducibility supports the candidacy of rs-fMRI outcome measures as biomarkers, but the presence of significant temporal structure needs to be taken into account when such outcome measures are considered as biomarkers for rehabilitation-style therapeutic interventions in chronic conditions. PMID:26517540

Regional homogeneity changes in prelingually deafened patients: a resting-state fMRI study

NASA Astrophysics Data System (ADS)

Li, Wenjing; He, Huiguang; Xian, Junfang; Lv, Bin; Li, Meng; Li, Yong; Liu, Zhaohui; Wang, Zhenchang

2010-03-01

Resting-state functional magnetic resonance imaging (fMRI) is a technique that measures the intrinsic function of brain and has some advantages over task-induced fMRI. Regional homogeneity (ReHo) assesses the similarity of the time series of a given voxel with its nearest neighbors on a voxel-by-voxel basis, which reflects the temporal homogeneity of the regional BOLD signal. In the present study, we used the resting state fMRI data to investigate the ReHo changes of the whole brain in the prelingually deafened patients relative to normal controls. 18 deaf patients and 22 healthy subjects were scanned. Kendall's coefficient of concordance (KCC) was calculated to measure the degree of regional coherence of fMRI time courses. We found that regional coherence significantly decreased in the left frontal lobe, bilateral temporal lobes and right thalamus, and increased in the postcentral gyrus, cingulate gyrus, left temporal lobe, left thalamus and cerebellum in deaf patients compared with controls. These results show that the prelingually deafened patients have higher degree of regional coherence in the paleocortex, and lower degree in neocortex. Since neocortex plays an important role in the development of auditory, these evidences may suggest that the deaf persons reorganize the paleocortex to offset the loss of auditory.

Follow-up of cortical activity and structure after lesion with laser speckle imaging and magnetic resonance imaging in nonhuman primates

NASA Astrophysics Data System (ADS)

Peuser, Jörn; Belhaj-Saif, Abderraouf; Hamadjida, Adjia; Schmidlin, Eric; Gindrat, Anne-Dominique; Völker, Andreas Charles; Zakharov, Pavel; Hoogewoud, Henri-Marcel; Rouiller, Eric M.; Scheffold, Frank

2011-09-01

The nonhuman primate model is suitable to study mechanisms of functional recovery following lesion of the cerebral cortex (motor cortex), on which therapeutic strategies can be tested. To interpret behavioral data (time course and extent of functional recovery), it is crucial to monitor the properties of the experimental cortical lesion, induced by infusion of the excitotoxin ibotenic acid. In two adult macaque monkeys, ibotenic acid infusions produced a restricted, permanent lesion of the motor cortex. In one monkey, the lesion was monitored over 3.5 weeks, combining laser speckle imaging (LSI) as metabolic readout (cerebral blood flow) and anatomical assessment with magnetic resonance imaging (T2-weighted MRI). The cerebral blood flow, measured online during subsequent injections of the ibotenic acid in the motor cortex, exhibited a dramatic increase, still present after one week, in parallel to a MRI hypersignal. After 3.5 weeks, the cerebral blood flow was strongly reduced (below reference level) and the hypersignal disappeared from the MRI scan, although the lesion was permanent as histologically assessed post-mortem. The MRI data were similar in the second monkey. Our experiments suggest that LSI and MRI, although they reflect different features, vary in parallel during a few weeks following an excitotoxic cortical lesion.

Resting States Are Resting Traits – An fMRI Study of Sex Differences and Menstrual Cycle Effects in Resting State Cognitive Control Networks

PubMed Central

Hjelmervik, Helene; Hausmann, Markus; Osnes, Berge; Westerhausen, René; Specht, Karsten

2014-01-01

To what degree resting state fMRI is stable or susceptible to internal mind states of the individual is currently an issue of debate. To address this issue, the present study focuses on sex differences and investigates whether resting state fMRI is stable in men and women or changes within relative short-term periods (i.e., across the menstrual cycle). Due to the fact that we recently reported menstrual cycle effects on cognitive control based on data collected during the same sessions, the current study is particularly interested in fronto-parietal resting state networks. Resting state fMRI was measured in sixteen women during three different cycle phases (menstrual, follicular, and luteal). Fifteen men underwent three sessions in corresponding time intervals. We used independent component analysis to identify four fronto-parietal networks. The results showed sex differences in two of these networks with women exhibiting higher functional connectivity in general, including the prefrontal cortex. Menstrual cycle effects on resting states were non-existent. It is concluded that sex differences in resting state fMRI might reflect sexual dimorphisms in the brain rather than transitory activating effects of sex hormones on the functional connectivity in the resting brain. PMID:25057823

Application of Independent Component Analysis for the Data Mining of Simultaneous EEG-fMRI: Preliminary Experience on Sleep Onset

PubMed Central

Lee, Jong-Hwan; Oh, Sungsuk; Jolesz, Ferenc A.; Park, Hyunwook; Yoo, Seung-Schik

2010-01-01

The simultaneous acquisition of electroencephalogram (EEG) and functional MRI (fMRI) signals is potentially advantageous because of the superior resolution that is achieved in both the temporal and spatial domains, respectively. However, ballistocardiographic artifacts along with the ocular artifacts are a major obstacle for the detection of the EEG signatures of interest. Since the sources corresponding to these artifacts are independent from those producing the EEG signatures, we applied the Infomax-based independent component analysis (ICA) technique to separate the EEG signatures from the artifacts. The isolated EEG signatures were further utilized to model the canonical hemodynamic response functions (HRFs). Subsequently, the brain areas from which these EEG signatures originated were identified as locales of activation patterns from the analysis of fMRI data. Upon the identification and subsequent evaluation of brain areas generating interictal epileptic discharge (IED) spikes from an epileptic subject, the presented method was successfully applied to detect the theta- and alpha-rhythms that are sleep onset related EEG signatures along with the subsequent neural circuitries from a sleep deprived volunteer. These results suggest that the ICA technique may be useful for the preprocessing of simultaneous EEG-fMRI acquisitions, especially when a reference paradigm is unavailable. PMID:19922343

Application of independent component analysis for the data mining of simultaneous Eeg-fMRI: preliminary experience on sleep onset.

PubMed

Lee, Jong-Hwan; Oh, Sungsuk; Jolesz, Ferenc A; Park, Hyunwook; Yoo, Seung-Schik

2009-01-01

The simultaneous acquisition of electroencephalogram (EEG) and functional MRI (fMRI) signals is potentially advantageous because of the superior resolution that is achieved in both the temporal and spatial domains, respectively. However, ballistocardiographic artifacts along with ocular artifacts are a major obstacle for the detection of the EEG signatures of interest. Since the sources corresponding to these artifacts are independent from those producing the EEG signatures, we applied the Infomax-based independent component analysis (ICA) technique to separate the EEG signatures from the artifacts. The isolated EEG signatures were further utilized to model the canonical hemodynamic response functions (HRFs). Subsequently, the brain areas from which these EEG signatures originated were identified as locales of activation patterns from the analysis of fMRI data. Upon the identification and subsequent evaluation of brain areas generating interictal epileptic discharge (IED) spikes from an epileptic subject, the presented method was successfully applied to detect the theta and alpha rhythms that are sleep onset-related EEG signatures along with the subsequent neural circuitries from a sleep-deprived volunteer. These results suggest that the ICA technique may be useful for the preprocessing of simultaneous EEG-fMRI acquisitions, especially when a reference paradigm is unavailable.

Utility of functional MRI in pediatric neurology.

PubMed

Freilich, Emily R; Gaillard, William D

2010-01-01

Functional MRI (fMRI), a tool increasingly used to study cognitive function, is also an important tool for understanding not only normal development in healthy children, but also abnormal development, as seen in children with epilepsy, attention-deficit/hyperactivity disorder, and autism. Since its inception almost 15 years ago, fMRI has seen an explosion in its use and applications in the adult literature. However, only recently has it found a home in pediatric neurology. New adaptations in study design and technologic advances, especially the study of resting state functional connectivity as well as the use of passive task design in sedated children, have increased the utility of functional imaging in pediatrics to help us gain understanding into the developing brain at work. This article reviews the background of fMRI in pediatrics and highlights the most recent literature and clinical applications.

Motion correction for functional MRI with three‐dimensional hybrid radial‐Cartesian EPI

PubMed Central

McNab, Jennifer A.; Chiew, Mark; Miller, Karla L.

2016-01-01

Purpose Subject motion is a major source of image degradation for functional MRI (fMRI), especially when using multishot sequences like three‐dimensional (3D EPI). We present a hybrid radial‐Cartesian 3D EPI trajectory enabling motion correction in k‐space for functional MRI. Methods The EPI “blades” of the 3D hybrid radial‐Cartesian EPI sequence, called TURBINE, are rotated about the phase‐encoding axis to fill out a cylinder in 3D k‐space. Angular blades are acquired over time using a golden‐angle rotation increment, allowing reconstruction at flexible temporal resolution. The self‐navigating properties of the sequence are used to determine motion parameters from a high temporal‐resolution navigator time series. The motion is corrected in k‐space as part of the image reconstruction, and evaluated for experiments with both cued and natural motion. Results We demonstrate that the motion correction works robustly and that we can achieve substantial artifact reduction as well as improvement in temporal signal‐to‐noise ratio and fMRI activation in the presence of both severe and subtle motion. Conclusion We show the potential for hybrid radial‐Cartesian 3D EPI to substantially reduce artifacts for application in fMRI, especially for subject groups with significant head motion. The motion correction approach does not prolong the scan, and no extra hardware is required. Magn Reson Med 78:527–540, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. PMID:27604503

Complete fourier direct magnetic resonance imaging (CFD-MRI) for diffusion MRI

PubMed Central

Özcan, Alpay

2013-01-01

The foundation for an accurate and unifying Fourier-based theory of diffusion weighted magnetic resonance imaging (DW–MRI) is constructed by carefully re-examining the first principles of DW–MRI signal formation and deriving its mathematical model from scratch. The derivations are specifically obtained for DW–MRI signal by including all of its elements (e.g., imaging gradients) using complex values. Particle methods are utilized in contrast to conventional partial differential equations approach. The signal is shown to be the Fourier transform of the joint distribution of number of the magnetic moments (at a given location at the initial time) and magnetic moment displacement integrals. In effect, the k-space is augmented by three more dimensions, corresponding to the frequency variables dual to displacement integral vectors. The joint distribution function is recovered by applying the Fourier transform to the complete high-dimensional data set. In the process, to obtain a physically meaningful real valued distribution function, phase corrections are applied for the re-establishment of Hermitian symmetry in the signal. Consequently, the method is fully unconstrained and directly presents the distribution of displacement integrals without any assumptions such as symmetry or Markovian property. The joint distribution function is visualized with isosurfaces, which describe the displacement integrals, overlaid on the distribution map of the number of magnetic moments with low mobility. The model provides an accurate description of the molecular motion measurements via DW–MRI. The improvement of the characterization of tissue microstructure leads to a better localization, detection and assessment of biological properties such as white matter integrity. The results are demonstrated on the experimental data obtained from an ex vivo baboon brain. PMID:23596401

Regional autonomy changes in resting-state functional MRI in patients with HIV associated neurocognitive disorder

NASA Astrophysics Data System (ADS)

DSouza, Adora M.; Abidin, Anas Z.; Chockanathan, Udaysankar; Wismüller, Axel

2018-03-01

In this study, we investigate whether there are discernable changes in influence that brain regions have on themselves once patients show symptoms of HIV Associated Neurocognitive Disorder (HAND) using functional MRI (fMRI). Simple functional connectivity measures, such as correlation cannot reveal such information. To this end, we use mutual connectivity analysis (MCA) with Local Models (LM), which reveals a measure of influence in terms of predictability. Once such measures of interaction are obtained, we train two classifiers to characterize difference in patterns of regional self-influence between healthy subjects and subjects presenting with HAND symptoms. The two classifiers we use are Support Vector Machines (SVM) and Localized Generalized Matrix Learning Vector Quantization (LGMLVQ). Performing machine learning on fMRI connectivity measures is popularly known as multi-voxel pattern analysis (MVPA). By performing such an analysis, we are interested in studying the impact HIV infection has on an individual's brain. The high area under receiver operating curve (AUC) and accuracy values for 100 different train/test separations using MCA-LM self-influence measures (SVM: mean AUC=0.86, LGMLVQ: mean AUC=0.88, SVM and LGMLVQ: mean accuracy=0.78) compared with standard MVPA analysis using cross-correlation between fMRI time-series (SVM: mean AUC=0.58, LGMLVQ: mean AUC=0.57), demonstrates that self-influence features can be more discriminative than measures of interaction between time-series pairs. Furthermore, our results suggest that incorporating measures of self-influence in MVPA analysis used commonly in fMRI analysis has the potential to provide a performance boost and indicate important changes in dynamics of regions in the brain as a consequence of HIV infection.

Resting-state functional MRI as a tool for evaluating brain hemodynamic responsiveness to external stimuli in rats.

PubMed

Paasonen, Jaakko; Salo, Raimo A; Huttunen, Joanna K; Gröhn, Olli

2017-09-01

Anesthesia is a major confounding factor in functional MRI (fMRI) experiments attributed to its effects on brain function. Recent evidence suggests that parameters obtained with resting-state fMRI (rs-fMRI) are coupled with anesthetic depth. Therefore, we investigated whether parameters obtained with rs-fMRI, such as functional connectivity (FC), are also directly related to blood-oxygen-level-dependent (BOLD) responses. A simple rs-fMRI protocol was implemented in a pharmacological fMRI study to evaluate the coupling between hemodynamic responses and FC under five anesthetics (α-chloralose, isoflurane, medetomidine, thiobutabarbital, and urethane). Temporal change in the FC was evaluated at 1-hour interval. Supplementary forepaw stimulation experiments were also conducted. Under thiobutabarbital anesthesia, FC was clearly coupled with nicotine-induced BOLD responses. Good correlation values were also obtained under isoflurane and medetomidine anesthesia. The observations in the thiobutabarbital group were supported by forepaw stimulation experiments. Additionally, the rs-fMRI protocol revealed significant temporal changes in the FC in the α-chloralose, thiobutabarbital, and urethane groups. Our results suggest that FC can be used to estimate brain hemodynamic responsiveness to stimuli and evaluate the level and temporal changes of anesthesia. Therefore, analysis of the fMRI baseline signal may be highly valuable tool for controlling the outcome of preclinical fMRI experiments. Magn Reson Med 78:1136-1146, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Integrating histology and MRI in the first digital brain of common squirrel monkey, Saimiri sciureus

NASA Astrophysics Data System (ADS)

Sun, Peizhen; Parvathaneni, Prasanna; Schilling, Kurt G.; Gao, Yurui; Janve, Vaibhav; Anderson, Adam; Landman, Bennett A.

2015-03-01

This effort is a continuation of development of a digital brain atlas of the common squirrel monkey, Saimiri sciureus, a New World monkey with functional and microstructural organization of central nervous system similar to that of humans. Here, we present the integration of histology with multi-modal magnetic resonance imaging (MRI) atlas constructed from the brain of an adult female squirrel monkey. The central concept of this work is to use block face photography to establish an intermediate common space in coordinate system which preserves the high resolution in-plane resolution of histology while enabling 3-D correspondence with MRI. In vivo MRI acquisitions include high resolution T2 structural imaging (300 μm isotropic) and low resolution diffusion tensor imaging (600 um isotropic). Ex vivo MRI acquisitions include high resolution T2 structural imaging and high resolution diffusion tensor imaging (both 300 μm isotropic). Cortical regions were manually annotated on the co-registered volumes based on published histological sections in-plane. We describe mapping of histology and MRI based data of the common squirrel monkey and construction of a viewing tool that enable online viewing of these datasets. The previously descried atlas MRI is used for its deformation to provide accurate conformation to the MRI, thus adding information at the histological level to the MRI volume. This paper presents the mapping of single 2D image slice in block face as a proof of concept and this can be extended to map the atlas space in 3D coordinate system as part of the future work and can be loaded to an XNAT system for further use.

Magnetic Resonance Imaging to Evaluate Cervical Spinal Cord Injury from Gunshot Wounds from Handguns.

PubMed

Slavin, Justin; Beaty, Narlin; Raghavan, Prashant; Sansur, Charles; Aarabi, Bizhan

2015-12-01

Patients presenting with gunshot wounds (GSWs) to the neck are difficult to assess because of their injuries are often severe and they are incompletely evaluated by computed tomography (CT) alone. Our institution treats hundreds of patients with GSWs each year and we present our experience using magnetic resonance imaging (MRI) in the evaluation of cervical GSWs. From August 2000 to July 2012, all GSWs to the cervical spine treated at our institution were cataloged. Seventeen patients had 1 or more MRI studies of the cervical spine. Informed consent was obtained before MRI indicating the risks of retained metal fragments in the setting of high magnetic fields. CT scans were obtained before and after MRI to document any possible migration of metal fragments. We documented patients' neurologic examination results before and after MRI and at follow-up. Patients' age range was 18-56 years (mean 29.8 years). Eleven of 17 patients had retained metal fragments seen on CT scan, including 3 patients with fragments within the spinal canal. No patient experienced a decline in neurologic function after MRI. No migration of retained fragments was observed. Fifteen of 17 patients returned for follow-up examinations, with an average follow-up interval of 39.1 weeks (range, 1.3-202.3 weeks; median, 8 weeks). For carefully selected patients, MRI can be an effective tool in assessing GSWs to the neck and it can significantly improve the evaluation and management of this cohort. No patient in our series experienced a complication related to MRI. Copyright © 2015 Elsevier Inc. All rights reserved.

Simultaneous GCaMP6-based fiber photometry and fMRI in rats.

PubMed

Liang, Zhifeng; Ma, Yuncong; Watson, Glenn D R; Zhang, Nanyin

2017-09-01

Understanding the relationship between neural and vascular signals is essential for interpretation of functional MRI (fMRI) results with respect to underlying neuronal activity. Simultaneously measuring neural activity using electrophysiology with fMRI has been highly valuable in elucidating the neural basis of the blood oxygenation-level dependent (BOLD) signal. However, this approach is also technically challenging due to the electromagnetic interference that is observed in electrophysiological recordings during MRI scanning. Recording optical correlates of neural activity, such as calcium signals, avoids this issue, and has opened a new avenue to simultaneously acquire neural and BOLD signals. The present study is the first to demonstrate the feasibility of simultaneously and repeatedly acquiring calcium and BOLD signals in animals using a genetically encoded calcium indicator, GCaMP6. This approach was validated with a visual stimulation experiment, during which robust increases of both calcium and BOLD signals in the superior colliculus were observed. In addition, repeated measurement in the same animal demonstrated reproducible calcium and BOLD responses to the same stimuli. Taken together, simultaneous GCaMP6-based fiber photometry and fMRI recording presents a novel, artifact-free approach to simultaneously measuring neural and fMRI signals. Furthermore, given the cell-type specificity of GCaMP6, this approach has the potential to mechanistically dissect the contributions of individual neuron populations to BOLD signal, and ultimately reveal its underlying neural mechanisms. The current study established the method for simultaneous GCaMP6-based fiber photometry and fMRI in rats. Copyright © 2017 Elsevier B.V. All rights reserved.

Fiber Optic Force Sensors for MRI-Guided Interventions and Rehabilitation: A Review

PubMed Central

Iordachita, Iulian I.; Tokuda, Junichi; Hata, Nobuhiko; Liu, Xuan; Seifabadi, Reza; Xu, Sheng; Wood, Bradford; Fischer, Gregory S.

2017-01-01

Magnetic Resonance Imaging (MRI) provides both anatomical imaging with excellent soft tissue contrast and functional MRI imaging (fMRI) of physiological parameters. The last two decades have witnessed the manifestation of increased interest in MRI-guided minimally invasive intervention procedures and fMRI for rehabilitation and neuroscience research. Accompanying the aspiration to utilize MRI to provide imaging feedback during interventions and brain activity for neuroscience study, there is an accumulated effort to utilize force sensors compatible with the MRI environment to meet the growing demand of these procedures, with the goal of enhanced interventional safety and accuracy, improved efficacy and rehabilitation outcome. This paper summarizes the fundamental principles, the state of the art development and challenges of fiber optic force sensors for MRI-guided interventions and rehabilitation. It provides an overview of MRI-compatible fiber optic force sensors based on different sensing principles, including light intensity modulation, wavelength modulation, and phase modulation. Extensive design prototypes are reviewed to illustrate the detailed implementation of these principles. Advantages and disadvantages of the sensor designs are compared and analyzed. A perspective on the future development of fiber optic sensors is also presented which may have additional broad clinical applications. Future surgical interventions or rehabilitation will rely on intelligent force sensors to provide situational awareness to augment or complement human perception in these procedures. PMID:28652857

Role of fMRI in the decision-making process: epilepsy surgery for children.

PubMed

Liégeois, Frédérique; Cross, J Helen; Gadian, David G; Connelly, Alan

2006-06-01

Functional MRI (fMRI) is increasingly being used to evaluate children and adolescents who are candidates for surgical treatment of intractable epilepsy. It has the advantage of being noninvasive and well tolerated by young people. By identifying important functional regions within the brain, including unpredictable patterns of functional reorganization, it can aid in surgical decision-making. Here we illustrate this using a number of case studies from the pediatric epilepsy surgery program at our institution. We describe how fMRI, used in conjunction with conventional investigative methods such as neuropsychological assessment, MRI, and electrophysiology, can 1) help to improve functional outcome by enabling resective surgery that spares functional cortex, 2) guide surgical intervention by revealing when reorganization of function has occurred, and 3) show when abnormal cortex is also functionally active, and hence that surgery may not be the best option. Altogether, these roles have reduced the need for invasive procedures that can be both risky and distressing for young people with epilepsy. In our experience, fMRI has significantly contributed to the decision-making process, and improved the counseling and management of young people with intractable epilepsy. Copyright 2006 Wiley-Liss, Inc.

Delineating potential epileptogenic areas utilizing resting functional magnetic resonance imaging (fMRI) in epilepsy patients.

PubMed

Pizarro, Ricardo; Nair, Veena; Meier, Timothy; Holdsworth, Ryan; Tunnell, Evelyn; Rutecki, Paul; Sillay, Karl; Meyerand, Mary E; Prabhakaran, Vivek

2016-08-01

Seizure localization includes neuroimaging like electroencephalogram, and magnetic resonance imaging (MRI) with limited ability to characterize the epileptogenic network. Temporal clustering analysis (TCA) characterizes epileptogenic network congruent with interictal epileptiform discharges by clustering together voxels with transient signals. We generated epileptogenic areas for 12 of 13 epilepsy patients with TCA, congruent with different areas of seizure onset. Resting functional MRI (fMRI) scans are noninvasive, and can be acquired quickly, in patients with different levels of severity and function. Analyzing resting fMRI data using TCA is quick and can complement clinical methods to characterize the epileptogenic network.

Correcting for Blood Arrival Time in Global Mean Regression Enhances Functional Connectivity Analysis of Resting State fMRI-BOLD Signals.

PubMed

Erdoğan, Sinem B; Tong, Yunjie; Hocke, Lia M; Lindsey, Kimberly P; deB Frederick, Blaise

2016-01-01

Resting state functional connectivity analysis is a widely used method for mapping intrinsic functional organization of the brain. Global signal regression (GSR) is commonly employed for removing systemic global variance from resting state BOLD-fMRI data; however, recent studies have demonstrated that GSR may introduce spurious negative correlations within and between functional networks, calling into question the meaning of anticorrelations reported between some networks. In the present study, we propose that global signal from resting state fMRI is composed primarily of systemic low frequency oscillations (sLFOs) that propagate with cerebral blood circulation throughout the brain. We introduce a novel systemic noise removal strategy for resting state fMRI data, "dynamic global signal regression" (dGSR), which applies a voxel-specific optimal time delay to the global signal prior to regression from voxel-wise time series. We test our hypothesis on two functional systems that are suggested to be intrinsically organized into anticorrelated networks: the default mode network (DMN) and task positive network (TPN). We evaluate the efficacy of dGSR and compare its performance with the conventional "static" global regression (sGSR) method in terms of (i) explaining systemic variance in the data and (ii) enhancing specificity and sensitivity of functional connectivity measures. dGSR increases the amount of BOLD signal variance being modeled and removed relative to sGSR while reducing spurious negative correlations introduced in reference regions by sGSR, and attenuating inflated positive connectivity measures. We conclude that incorporating time delay information for sLFOs into global noise removal strategies is of crucial importance for optimal noise removal from resting state functional connectivity maps.

Au Nanocage Functionalized with Ultra-small Fe3O4 Nanoparticles for Targeting T1-T2Dual MRI and CT Imaging of Tumor

NASA Astrophysics Data System (ADS)

Wang, Guannan; Gao, Wei; Zhang, Xuanjun; Mei, Xifan

2016-06-01

Diagnostic approaches based on multimodal imaging of clinical noninvasive imaging (eg. MRI/CT scanner) are highly developed in recent years for accurate selection of the therapeutic regimens in critical diseases. Therefore, it is highly demanded in the development of appropriate all-in-one multimodal contrast agents (MCAs) for the MRI/CT multimodal imaging. Here a novel ideal MCAs (F-AuNC@Fe3O4) were engineered by assemble Au nanocages (Au NC) and ultra-small iron oxide nanoparticles (Fe3O4) for simultaneous T1-T2dual MRI and CT contrast imaging. In this system, the Au nanocages offer facile thiol modification and strong X-ray attenuation property for CT imaging. The ultra-small Fe3O4 nanoparticles, as excellent contrast agent, is able to provide great enhanced signal of T1- and T2-weighted MRI (r1 = 6.263 mM-1 s-1, r2 = 28.117 mM-1 s-1) due to their ultra-refined size. After functionalization, the present MCAs nanoparticles exhibited small average size, low aggregation and excellent biocompatible. In vitro and In vivo studies revealed that the MCAs show long-term circulation time, renal clearance properties and outstanding capability of selective accumulation in tumor tissues for simultaneous CT imaging and T1- and T2-weighted MRI. Taken together, these results show that as-prepared MCAs are excellent candidates as MRI/CT multimodal imaging contrast agents.

Brain regions implicated in inhibitory control and appetite regulation are activated in response to food portion size and energy density in children.

PubMed

English, L K; Fearnbach, S N; Lasschuijt, M; Schlegel, A; Anderson, K; Harris, S; Wilson, S J; Fisher, J O; Savage, J S; Rolls, B J; Keller, K L

2016-10-01

Large portions of energy-dense foods drive energy intake but the brain mechanisms underlying this effect are not clear. Our main objective was to investigate brain function in response to food images varied by portion size (PS) and energy density (ED) in children using functional magnetic resonance imaging (fMRI). Blood-oxygen-level-dependent (BOLD) fMRI was completed in 36 children (ages 7-10 years) after a 2-h fast while viewing food images at two levels of PS (Large PS, Small PS) and two levels of ED (High ED, Low ED). Children rated perceived fullness pre- and post-fMRI, as well as liking of images on visual analog scales post-fMRI. Anthropometrics were completed 4 weeks before the fMRI. Large PS vs Small PS and High ED vs Low ED were compared with region-of-interest analyses using Brain Voyager v 2.8. Region-of-interest analyses revealed that activation in the right inferior frontal gyrus (P=0.03) was greater for Large PS vs Small PS. Activation was reduced for High ED vs Low ED in the left hypothalamus (P=0.03). Main effects were no longer significant after adjustment for pre-fMRI fullness and liking ratings (PS, P=0.92; ED, P=0.58). This is the first fMRI study to report increased activation to large portions in a brain region that is involved in inhibitory control. These findings may contribute to understanding why some children overeat when presented with large portions of palatable food.

An 8/15-channel Tx/Rx head neck RF coil combination with region-specific B1 + shimming for whole-brain MRI focused on the cerebellum at 7T.

PubMed

Pfaffenrot, Viktor; Brunheim, Sascha; Rietsch, Stefan H G; Koopmans, Peter J; Ernst, Thomas M; Kraff, Oliver; Orzada, Stephan; Quick, Harald H

2018-02-09

To design and evaluate an 8/15-channel transmit/receive (Tx/Rx) head-neck RF coil combination with region-specific B1+ shimming for whole-brain MRI with focus on improved functional MRI of the cerebellum at 7 T. An 8-channel transceiver RF head coil was combined with a 7-channel receive-only array. The noise parameters and acceleration capabilities of this 8Tx/15Rx coil setup were compared with a commercially available 1Tx/32Rx RF head coil. Region-specific 8-channel B1+ shimming was applied when using the 8Tx/15Rx RF coil. To evaluate the capability for functional MRI of the cerebellum, temporal SNR and statistical nonparametric maps for finger-tapping experiments with 14 healthy subjects were derived by applying a variable slice thickness gradient-echo echo-planar functional MRI sequence. The 8Tx/15Rx setup had a lower maximum noise correlation between channels, but higher average correlations compared with the 1Tx/32Rx coil. Both RF coils exhibited identical g-factors in the cerebellum with R = 3 acceleration. The enlarged FOV of the 8Tx/15Rx coil in combination with region-specific B1+ shimming increased homogeneity of the transmission field and temporal SNR in caudal cerebellar regions. Temporal SNR losses in cranial parts were reduced, resulting in more highly significant voxels in the caudally activated areas and identical patterns in the cranial cerebellar parts during a finger-tapping task. Compared with the 1Tx/32Rx RF coil, the presented 8Tx/15Rx RF coil combination successfully improves functional MRI of the human cerebellum at 7 T while maintaining whole-brain coverage. A clear temporal SNR gain in caudal cerebellar regions is shown. © 2018 International Society for Magnetic Resonance in Medicine.

Surface-Based fMRI-Driven Diffusion Tractography in the Presence of Significant Brain Pathology: A Study Linking Structure and Function in Cerebral Palsy

PubMed Central

Cunnington, Ross; Boyd, Roslyn N.; Rose, Stephen E.

2016-01-01

Diffusion MRI (dMRI) tractography analyses are difficult to perform in the presence of brain pathology. Automated methods that rely on cortical parcellation for structural connectivity studies often fail, while manually defining regions is extremely time consuming and can introduce human error. Both methods also make assumptions about structure-function relationships that may not hold after cortical reorganisation. Seeding tractography with functional-MRI (fMRI) activation is an emerging method that reduces these confounds, but inherent smoothing of fMRI signal may result in the inclusion of irrelevant pathways. This paper describes a novel fMRI-seeded dMRI-analysis pipeline based on surface-meshes that reduces these issues and utilises machine-learning to generate task specific white matter pathways, minimising the requirement for manually-drawn ROIs. We directly compared this new strategy to a standard voxelwise fMRI-dMRI approach, by investigating correlations between clinical scores and dMRI metrics of thalamocortical and corticomotor tracts in 31 children with unilateral cerebral palsy. The surface-based approach successfully processed more participants (87%) than the voxel-based approach (65%), and provided significantly more-coherent tractography. Significant correlations between dMRI metrics and five clinical scores of function were found for the more superior regions of these tracts. These significant correlations were stronger and more frequently found with the surface-based method (15/20 investigated were significant; R2 = 0.43–0.73) than the voxelwise analysis (2 sig. correlations; 0.38 & 0.49). More restricted fMRI signal, better-constrained tractography, and the novel track-classification method all appeared to contribute toward these differences. PMID:27487011

Synchronized delta oscillations correlate with the resting-state functional MRI signal

PubMed Central

Lu, Hanbing; Zuo, Yantao; Gu, Hong; Waltz, James A.; Zhan, Wang; Scholl, Clara A.; Rea, William; Yang, Yihong; Stein, Elliot A.

2007-01-01

Synchronized low-frequency spontaneous fluctuations of the functional MRI (fMRI) signal have recently been applied to investigate large-scale neuronal networks of the brain in the absence of specific task instructions. However, the underlying neural mechanisms of these fluctuations remain largely unknown. To this end, electrophysiological recordings and resting-state fMRI measurements were conducted in α-chloralose-anesthetized rats. Using a seed-voxel analysis strategy, region-specific, anesthetic dose-dependent fMRI resting-state functional connectivity was detected in bilateral primary somatosensory cortex (S1FL) of the resting brain. Cortical electroencephalographic signals were also recorded from bilateral S1FL; a visual cortex locus served as a control site. Results demonstrate that, unlike the evoked fMRI response that correlates with power changes in the γ bands, the resting-state fMRI signal correlates with the power coherence in low-frequency bands, particularly the δ band. These data indicate that hemodynamic fMRI signal differentially registers specific electrical oscillatory frequency band activity, suggesting that fMRI may be able to distinguish the ongoing from the evoked activity of the brain. PMID:17991778

Structural and functional network connectivity breakdown in Alzheimer’s disease studied with magnetic resonance imaging techniques.

PubMed

Filippi, Massimo; Agosta, Federica

2011-01-01

Patients with Alzheimer’s disease (AD) experience a brain network breakdown, reflecting disconnection at both the structural and functional system level. Resting-state (RS) functional MRI (fMRI) studies demonstrated that the regional coherence of the fMRI signal is significantly altered in patients with AD and amnestic mild cognitive impairment. Diffusion tensor (DT) MRI has made it possible to track fiber bundle projections across the brain, revealing a substantially abnormal interplay of “critical” white matter tracts in these conditions. The observed agreement between the results of RS fMRI and DT MRI tractography studies in healthy individuals is encouraging and offers interesting hypotheses to be tested in patients with AD, a MCI, and other dementias in order to improve our understanding of their pathobiology in vivo. In this review,we describe the major findings obtained in AD using RS fMRI and DT MRI tractography, and discuss how the relationship between structure and function of the brain networks in AD may be better understood through the application of MR-based technology. This research endeavor holds a great promise in clarifying the mechanisms of cognitive decline in complex chronic neurodegenerative disorders.

Functional localization of the human color center by decreased water displacement using diffusion-weighted fMRI.

PubMed

Williams, Rebecca J; Reutens, David C; Hocking, Julia

2015-11-01

Decreased water displacement following increased neural activity has been observed using diffusion-weighted functional MRI (DfMRI) at high b-values. The physiological mechanisms underlying the diffusion signal change may be unique from the standard blood oxygenation level-dependent (BOLD) contrast and closer to the source of neural activity. Whether DfMRI reflects neural activity more directly than BOLD outside the primary cerebral regions remains unclear. Colored and achromatic Mondrian visual stimuli were statistically contrasted to functionally localize the human color center Area V4 in neurologically intact adults. Spatial and temporal properties of DfMRI and BOLD activation were examined across regions of the visual cortex. At the individual level, DfMRI activation patterns showed greater spatial specificity to V4 than BOLD. The BOLD activation patterns were more prominent in the primary visual cortex than DfMRI, where activation was localized to the ventral temporal lobe. Temporally, the diffusion signal change in V4 and V1 both preceded the corresponding hemodynamic response, however the early diffusion signal change was more evident in V1. DfMRI may be of use in imaging applications implementing cognitive subtraction paradigms, and where highly precise individual functional localization is required.

Interplay between Functional Connectivity and Scale-Free Dynamics in Intrinsic fMRI Networks

PubMed Central

Ciuciu, Philippe; Abry, Patrice; He, Biyu J.

2014-01-01

Studies employing functional connectivity-type analyses have established that spontaneous fluctuations in functional magnetic resonance imaging (fMRI) signals are organized within large-scale brain networks. Meanwhile, fMRI signals have been shown to exhibit 1/f-type power spectra – a hallmark of scale-free dynamics. We studied the interplay between functional connectivity and scale-free dynamics in fMRI signals, utilizing the fractal connectivity framework – a multivariate extension of the univariate fractional Gaussian noise model, which relies on a wavelet formulation for robust parameter estimation. We applied this framework to fMRI data acquired from healthy young adults at rest and performing a visual detection task. First, we found that scale-invariance existed beyond univariate dynamics, being present also in bivariate cross-temporal dynamics. Second, we observed that frequencies within the scale-free range do not contribute evenly to inter-regional connectivity, with a systematically stronger contribution of the lowest frequencies, both at rest and during task. Third, in addition to a decrease of the Hurst exponent and inter-regional correlations, task performance modified cross-temporal dynamics, inducing a larger contribution of the highest frequencies within the scale-free range to global correlation. Lastly, we found that across individuals, a weaker task modulation of the frequency contribution to inter-regional connectivity was associated with better task performance manifesting as shorter and less variable reaction times. These findings bring together two related fields that have hitherto been studied separately – resting-state networks and scale-free dynamics, and show that scale-free dynamics of human brain activity manifest in cross-regional interactions as well. PMID:24675649

Fusing EEG and fMRI based on a bottom-up model: inferring activation and effective connectivity in neural masses

PubMed Central

Riera, J; Aubert, E; Iwata, K; Kawashima, R; Wan, X; Ozaki, T

2005-01-01

The elucidation of the complex machinery used by the human brain to segregate and integrate information while performing high cognitive functions is a subject of imminent future consequences. The most significant contributions to date in this field, known as cognitive neuroscience, have been achieved by using innovative neuroimaging techniques, such as electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI), which measure variations in both the time and the space of some interpretable physical magnitudes. Extraordinary maps of cerebral activation involving function-restricted brain areas, as well as graphs of the functional connectivity between them, have been obtained from EEG and fMRI data by solving some spatio-temporal inverse problems, which constitutes a top-down approach. However, in many cases, a natural bridge between these maps/graphs and the causal physiological processes is lacking, leading to some misunderstandings in their interpretation. Recent advances in the comprehension of the underlying physiological mechanisms associated with different cerebral scales have provided researchers with an excellent scenario to develop sophisticated biophysical models that permit an integration of these neuroimage modalities, which must share a common aetiology. This paper proposes a bottom-up approach, involving physiological parameters in a specific mesoscopic dynamic equations system. Further observation equations encapsulating the relationship between the mesostates and the EEG/fMRI data are obtained on the basis of the physical foundations of these techniques. A methodology for the estimation of parameters from fused EEG/fMRI data is also presented. In this context, the concepts of activation and effective connectivity are carefully revised. This new approach permits us to examine and discuss some future prospects for the integration of multimodal neuroimages. PMID:16087446

Neural correlates of social motivation: an fMRI study on power versus affiliation.

PubMed

Quirin, Markus; Meyer, Frank; Heise, Nils; Kuhl, Julius; Küstermann, Ekkehard; Strüber, Daniel; Cacioppo, John T

2013-06-01

Power versus affiliation motivations refer to two different strivings relevant in the context of social relationships. We used functional magnetic resonance imaging (fMRI) to determine neural structures involved in power versus affiliation motivation based on an individual differences approach. Seventeen participants provided self-reports of power and affiliation motives and were presented with love, power-related, and control movie clips. The power motive predicted activity in four clusters within the left prefrontal cortex (PFC), while participants viewed power-related film clips. The affiliation motive predicted activity in the right putamen/pallidum while participants viewed love stories. The present findings extend previous research on social motivations to the level of neural functioning and suggest differential networks for power-related versus affiliation-related social motivations. Copyright © 2012 Elsevier B.V. All rights reserved.

Subliminal versus supraliminal stimuli activate neural responses in anterior cingulate cortex, fusiform gyrus and insula: a meta-analysis of fMRI studies.

PubMed

Meneguzzo, Paolo; Tsakiris, Manos; Schioth, Helgi B; Stein, Dan J; Brooks, Samantha J

2014-01-01

Non-conscious neural activation may underlie various psychological functions in health and disorder. However, the neural substrates of non-conscious processing have not been entirely elucidated. Examining the differential effects of arousing stimuli that are consciously, versus unconsciously perceived will improve our knowledge of neural circuitry involved in non-conscious perception. Here we conduct preliminary analyses of neural activation in studies that have used both subliminal and supraliminal presentation of the same stimulus. We use Activation Likelihood Estimation (ALE) to examine functional Magnetic Resonance Imaging (fMRI) studies that uniquely present the same stimuli subliminally and supraliminally to healthy participants during functional magnetic resonance imaging (fMRI). We included a total of 193 foci from 9 studies representing subliminal stimulation and 315 foci from 10 studies representing supraliminal stimulation. The anterior cingulate cortex is significantly activated during both subliminal and supraliminal stimulus presentation. Subliminal stimuli are linked to significantly increased activation in the right fusiform gyrus and right insula. Supraliminal stimuli show significantly increased activation in the left rostral anterior cingulate. Non-conscious processing of arousing stimuli may involve primary visual areas and may also recruit the insula, a brain area involved in eventual interoceptive awareness. The anterior cingulate is perhaps a key brain region for the integration of conscious and non-conscious processing. These preliminary data provide candidate brain regions for further study in to the neural correlates of conscious experience.

A general prediction model for the detection of ADHD and Autism using structural and functional MRI.

PubMed

Sen, Bhaskar; Borle, Neil C; Greiner, Russell; Brown, Matthew R G

2018-01-01

This work presents a novel method for learning a model that can diagnose Attention Deficit Hyperactivity Disorder (ADHD), as well as Autism, using structural texture and functional connectivity features obtained from 3-dimensional structural magnetic resonance imaging (MRI) and 4-dimensional resting-state functional magnetic resonance imaging (fMRI) scans of subjects. We explore a series of three learners: (1) The LeFMS learner first extracts features from the structural MRI images using the texture-based filters produced by a sparse autoencoder. These filters are then convolved with the original MRI image using an unsupervised convolutional network. The resulting features are used as input to a linear support vector machine (SVM) classifier. (2) The LeFMF learner produces a diagnostic model by first computing spatial non-stationary independent components of the fMRI scans, which it uses to decompose each subject's fMRI scan into the time courses of these common spatial components. These features can then be used with a learner by themselves or in combination with other features to produce the model. Regardless of which approach is used, the final set of features are input to a linear support vector machine (SVM) classifier. (3) Finally, the overall LeFMSF learner uses the combined features obtained from the two feature extraction processes in (1) and (2) above as input to an SVM classifier, achieving an accuracy of 0.673 on the ADHD-200 holdout data and 0.643 on the ABIDE holdout data. Both of these results, obtained with the same LeFMSF framework, are the best known, over all hold-out accuracies on these datasets when only using imaging data-exceeding previously-published results by 0.012 for ADHD and 0.042 for Autism. Our results show that combining multi-modal features can yield good classification accuracy for diagnosis of ADHD and Autism, which is an important step towards computer-aided diagnosis of these psychiatric diseases and perhaps others as well.

Pediatric functional magnetic resonance neuroimaging: tactics for encouraging task compliance.

PubMed

Schlund, Michael W; Cataldo, Michael F; Siegle, Greg J; Ladouceur, Cecile D; Silk, Jennifer S; Forbes, Erika E; McFarland, Ashley; Iyengar, Satish; Dahl, Ronald E; Ryan, Neal D

2011-05-06

Neuroimaging technology has afforded advances in our understanding of normal and pathological brain function and development in children and adolescents. However, noncompliance involving the inability to remain in the magnetic resonance imaging (MRI) scanner to complete tasks is one common and significant problem. Task noncompliance is an especially significant problem in pediatric functional magnetic resonance imaging (fMRI) research because increases in noncompliance produces a greater risk that a study sample will not be representative of the study population. In this preliminary investigation, we describe the development and application of an approach for increasing the number of fMRI tasks children complete during neuroimaging. Twenty-eight healthy children ages 9-13 years participated. Generalization of the approach was examined in additional fMRI and event-related potential investigations with children at risk for depression, children with anxiety and children with depression (N=120). Essential features of the approach include a preference assessment for identifying multiple individualized rewards, increasing reinforcement rates during imaging by pairing tasks with chosen rewards and presenting a visual 'road map' listing tasks, rewards and current progress. Our results showing a higher percentage of fMRI task completion by healthy children provides proof of concept data for the recommended tactics. Additional support was provided by results showing our approach generalized to several additional fMRI and event-related potential investigations and clinical populations. We proposed that some forms of task noncompliance may emerge from less than optimal reward protocols. While our findings may not directly support the effectiveness of the multiple reward compliance protocol, increased attention to how rewards are selected and delivered may aid cooperation with completing fMRI tasks. The proposed approach contributes to the pediatric neuroimaging literature by providing a useful way to conceptualize and measure task noncompliance and by providing simple cost effective tactics for improving the effectiveness of common reward-based protocols.

Correspondence between retinotopic cortical mapping and conventional functional and morphological assessment of retinal disease.

PubMed

Ritter, Markus; Hummer, Allan; Ledolter, Anna A; Holder, Graham E; Windischberger, Christian; Schmidt-Erfurth, Ursula M

2018-04-26

The present study describes retinotopic mapping of the primary visual cortex using functional MRI (fMRI) in patients with retinal disease. It addresses the relationship between fMRI data and data obtained by conventional assessment including microperimetry (MP) and structural imaging. Initial testing involved eight patients with central retinal disease (Stargardt disease, STGD) and eight with peripheral retinal disease (retinitis pigmentosa, RP), who were examined using fMRI and MP (Nidek MP-1). All had a secure clinical diagnosis supported by electrophysiological data. fMRI used population-receptive field (pRF) mapping to provide retinotopic data that were then compared with the results of MP, optical coherence tomography and fundus autofluorescence imaging. Full analysis, following assessment of fMRI data reliability criteria, was performed in five patients with STGD and seven patients with RP; unstable fixation was responsible for unreliable pRF measurements in three patients excluded from final analysis. The macular regions in patients with STGD with central visual field defects and outer retinal atrophy (ORA) at the macula correlated well with pRF coverage maps showing reduced density of activated voxels at the occipital pole. Patients with RP exhibited peripheral ORA and concentric visual field defects both on MP and pRF mapping. Anterior V1 voxels, corresponding to peripheral regions, showed no significant activation. Correspondence between MP and pRF mapping was quantified by calculating the simple matching coefficient. Retinotopic maps acquired by fMRI provide a valuable adjunct in the assessment of retinal dysfunction. The addition of microperimetric data to pRF maps allowed better assessment of macular function than MP alone. Unlike MP, pRF mapping provides objective data independent of psychophysical perception from the patient. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Pediatric functional magnetic resonance neuroimaging: tactics for encouraging task compliance

PubMed Central

2011-01-01

Background Neuroimaging technology has afforded advances in our understanding of normal and pathological brain function and development in children and adolescents. However, noncompliance involving the inability to remain in the magnetic resonance imaging (MRI) scanner to complete tasks is one common and significant problem. Task noncompliance is an especially significant problem in pediatric functional magnetic resonance imaging (fMRI) research because increases in noncompliance produces a greater risk that a study sample will not be representative of the study population. Method In this preliminary investigation, we describe the development and application of an approach for increasing the number of fMRI tasks children complete during neuroimaging. Twenty-eight healthy children ages 9-13 years participated. Generalization of the approach was examined in additional fMRI and event-related potential investigations with children at risk for depression, children with anxiety and children with depression (N = 120). Essential features of the approach include a preference assessment for identifying multiple individualized rewards, increasing reinforcement rates during imaging by pairing tasks with chosen rewards and presenting a visual 'road map' listing tasks, rewards and current progress. Results Our results showing a higher percentage of fMRI task completion by healthy children provides proof of concept data for the recommended tactics. Additional support was provided by results showing our approach generalized to several additional fMRI and event-related potential investigations and clinical populations. Discussion We proposed that some forms of task noncompliance may emerge from less than optimal reward protocols. While our findings may not directly support the effectiveness of the multiple reward compliance protocol, increased attention to how rewards are selected and delivered may aid cooperation with completing fMRI tasks Conclusion The proposed approach contributes to the pediatric neuroimaging literature by providing a useful way to conceptualize and measure task noncompliance and by providing simple cost effective tactics for improving the effectiveness of common reward-based protocols. PMID:21548928

WE-EF-BRD-03: I Want It Now!: Advances in MRI Acquisition, Reconstruction and the Use of Priors to Enable Fast Anatomic and Physiologic Imaging to Inform Guidance and Adaptation Decisions

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

Hu, Y.

MRI-guided treatment is a growing area of medicine, particularly in radiotherapy and surgery. The exquisite soft tissue anatomic contrast offered by MRI, along with functional imaging, makes the use of MRI during therapeutic procedures very attractive. Challenging the utility of MRI in the therapy room are many issues including the physics of MRI and the impact on the environment and therapeutic instruments, the impact of the room and instruments on the MRI; safety, space, design and cost. In this session, the applications and challenges of MRI-guided treatment will be described. The session format is: Past, present and future: MRI-guided radiotherapymore » from 2005 to 2025: Jan Lagendijk Battling Maxwell’s equations: Physics challenges and solutions for hybrid MRI systems: Paul Keall I want it now!: Advances in MRI acquisition, reconstruction and the use of priors to enable fast anatomic and physiologic imaging to inform guidance and adaptation decisions: Yanle Hu MR in the OR: The growth and applications of MRI for interventional radiology and surgery: Rebecca Fahrig Learning Objectives: To understand the history and trajectory of MRI-guided radiotherapy To understand the challenges of integrating MR imaging systems with linear accelerators To understand the latest in fast MRI methods to enable the visualisation of anatomy and physiology on radiotherapy treatment timescales To understand the growing role and challenges of MRI for image-guided surgical procedures My disclosures are publicly available and updated at: http://sydney.edu.au/medicine/radiation-physics/about-us/disclosures.php.« less

Portable MRI

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

Espy, Michelle A.

This project proposes to: (1) provide the power of MRI to situations where it presently isn't available; (2) perform the engineering required to move from lab to a functional prototype; and (3) leverage significant existing infrastructure and capability in ultra-low field MRI. The reasons for doing this: (1) MRI is the most powerful tool for imaging soft-tissue (e.g. brain); (2) Billions don't have access due to cost or safety issues; (3) metal will heat/move in high magnetic fields; (4) Millions of cases of traumatic brain injury in US alone; (5) even more of non-traumatic brain injury; (6) (e.g. stroke, infection,more » chemical exposure); (7) Need for early diagnostic; (8) 'Signature' wound of recent conflicts; (9) 22% of injuries; (10) Implications for post-traumatic stress disorder; and (11) chronic traumatic encephalopathy.« less

Training Efficiency and Transfer Success in an Extended Real-Time Functional MRI Neurofeedback Training of the Somatomotor Cortex of Healthy Subjects

PubMed Central

Auer, Tibor; Schweizer, Renate; Frahm, Jens

2015-01-01

This study investigated the level of self-regulation of the somatomotor cortices (SMCs) attained by an extended functional magnetic resonance imaging (fMRI) neurofeedback training. Sixteen healthy subjects performed 12 real-time functional magnetic resonance imaging neurofeedback training sessions within 4 weeks, involving motor imagery of the dominant right as well as the non-dominant left hand. Target regions of interests in the SMC were individually localized prior to the training by overt finger movements. The feedback signal (FS) was defined as the difference between fMRI activation in the contra- and ipsilateral SMC and visually presented to the subjects. Training efficiency was determined by an off-line general linear model analysis determining the fMRI percent signal changes in the SMC target areas accomplished during the neurofeedback training. Transfer success was assessed by comparing the pre- and post-training transfer task, i.e., the neurofeedback paradigm without the presentation of the FS. Group results show a distinct increase in feedback performance (FP) in the transfer task for the trained group compared to a matched untrained control group, as well as an increase in the time course of the training, indicating an efficient training and a successful transfer. Individual analysis revealed that the training efficiency was not only highly correlated to the transfer success but also predictive. Trainings with at least 12 efficient training runs were associated with a successful transfer outcome. A group analysis of the hemispheric contributions to the FP showed that it is mainly driven by increased fMRI activation in the contralateral SMC, although some individuals relied on ipsilateral deactivation. Training and transfer results showed no difference between left- and right-hand imagery, with a slight indication of more ipsilateral deactivation in the early right-hand trainings. PMID:26500521

Impact of Autocorrelation on Functional Connectivity

PubMed Central

Arbabshirani, Mohammad R.; Damaraju, Eswar; Phlypo, Ronald; Plis, Sergey; Allen, Elena; Ma, Sai; Mathalon, Daniel; Preda, Adrian; Vaidya, Jatin G.; Adali, Tülay; Calhoun, Vince D.

2014-01-01

Although the impact of serial correlation (autocorrelation) in residuals of general linear models for fMRI time-series has been studied extensively, the effect of autocorrelation on functional connectivity studies has been largely neglected until recently. Some recent studies based on results from economics have questioned the conventional estimation of functional connectivity and argue that not correcting for autocorrelation in fMRI time-series results in “spurious” correlation coefficients. In this paper, first we assess the effect of autocorrelation on Pearson correlation coefficient through theoretical approximation and simulation. Then we present this effect on real fMRI data. To our knowledge this is the first work comprehensively investigating the effect of autocorrelation on functional connectivity estimates. Our results show that although FC values are altered, even following correction for autocorrelation, results of hypothesis testing on FC values remain very similar to those before correction. In real data we show this is true for main effects and also for group difference testing between healthy controls and schizophrenia patients. We further discuss model order selection in the context of autoregressive processes, effects of frequency filtering and propose a preprocessing pipeline for connectivity studies. PMID:25072392

Composite iron oxide-Prussian blue nanoparticles for magnetically guided T1-weighted magnetic resonance imaging and photothermal therapy of tumors.

PubMed

Kale, Shraddha S; Burga, Rachel A; Sweeney, Elizabeth E; Zun, Zungho; Sze, Raymond W; Tuesca, Anthony; Subramony, J Anand; Fernandes, Rohan

2017-01-01

Theranostic nanoparticles offer the potential for mixing and matching disparate diagnostic and therapeutic functionalities within a single nanoparticle for the personalized treatment of diseases. In this article, we present composite iron oxide-gadolinium-containing Prussian blue nanoparticles (Fe 3 O 4 @GdPB) as a novel theranostic agent for T 1 -weighted magnetic resonance imaging (MRI) and photothermal therapy (PTT) of tumors. These particles combine the well-described properties and safety profiles of the constituent Fe 3 O 4 nanoparticles and gadolinium-containing Prussian blue nanoparticles. The Fe 3 O 4 @GdPB nanoparticles function both as effective MRI contrast agents and PTT agents as determined by characterizing studies performed in vitro and retain their properties in the presence of cells. Importantly, the Fe 3 O 4 @GdPB nanoparticles function as effective MRI contrast agents in vivo by increasing signal:noise ratios in T 1 -weighted scans of tumors and as effective PTT agents in vivo by decreasing tumor growth rates and increasing survival in an animal model of neuroblastoma. These findings demonstrate the potential of the Fe 3 O 4 @GdPB nanoparticles to function as effective theranostic agents.

Resting state activity in patients with disorders of consciousness

PubMed Central

Soddu, Andrea; Vanhaudenhuyse, Audrey; Demertzi, Athena; Bruno, Marie-Aurélie; Tshibanda, Luaba; Di, Haibo; Boly, Mélanie; Papa, Michele; Laureys, Steven; Noirhomme, Quentin

Summary Recent advances in the study of spontaneous brain activity have demonstrated activity patterns that emerge with no task performance or sensory stimulation; these discoveries hold promise for the study of higher-order associative network functionality. Additionally, such advances are argued to be relevant in pathological states, such as disorders of consciousness (DOC), i.e., coma, vegetative and minimally conscious states. Recent studies on resting state activity in DOC, measured with functional magnetic resonance imaging (fMRI) techniques, show that functional connectivity is disrupted in the task-negative or the default mode network. However, the two main approaches employed in the analysis of resting state functional connectivity data (i.e., hypothesis-driven seed-voxel and data-driven independent component analysis) present multiple methodological difficulties, especially in non-collaborative DOC patients. Improvements in motion artifact removal and spatial normalization are needed before fMRI resting state data can be used as proper biomarkers in severe brain injury. However, we anticipate that such developments will boost clinical resting state fMRI studies, allowing for easy and fast acquisitions and ultimately improve the diagnosis and prognosis in the absence of DOC patients’ active collaboration in data acquisition. PMID:21693087

Composite iron oxide–Prussian blue nanoparticles for magnetically guided T1-weighted magnetic resonance imaging and photothermal therapy of tumors

PubMed Central

Kale, Shraddha S; Burga, Rachel A; Sweeney, Elizabeth E; Zun, Zungho; Sze, Raymond W; Tuesca, Anthony; Subramony, J Anand; Fernandes, Rohan

2017-01-01

Theranostic nanoparticles offer the potential for mixing and matching disparate diagnostic and therapeutic functionalities within a single nanoparticle for the personalized treatment of diseases. In this article, we present composite iron oxide-gadolinium-containing Prussian blue nanoparticles (Fe3O4@GdPB) as a novel theranostic agent for T1-weighted magnetic resonance imaging (MRI) and photothermal therapy (PTT) of tumors. These particles combine the well-described properties and safety profiles of the constituent Fe3O4 nanoparticles and gadolinium-containing Prussian blue nanoparticles. The Fe3O4@GdPB nanoparticles function both as effective MRI contrast agents and PTT agents as determined by characterizing studies performed in vitro and retain their properties in the presence of cells. Importantly, the Fe3O4@GdPB nanoparticles function as effective MRI contrast agents in vivo by increasing signal:noise ratios in T1-weighted scans of tumors and as effective PTT agents in vivo by decreasing tumor growth rates and increasing survival in an animal model of neuroblastoma. These findings demonstrate the potential of the Fe3O4@GdPB nanoparticles to function as effective theranostic agents. PMID:28919744

Spatio-temporal models of mental processes from fMRI.

PubMed

Janoos, Firdaus; Machiraju, Raghu; Singh, Shantanu; Morocz, Istvan Ákos

2011-07-15

Understanding the highly complex, spatially distributed and temporally organized phenomena entailed by mental processes using functional MRI is an important research problem in cognitive and clinical neuroscience. Conventional analysis methods focus on the spatial dimension of the data discarding the information about brain function contained in the temporal dimension. This paper presents a fully spatio-temporal multivariate analysis method using a state-space model (SSM) for brain function that yields not only spatial maps of activity but also its temporal structure along with spatially varying estimates of the hemodynamic response. Efficient algorithms for estimating the parameters along with quantitative validations are given. A novel low-dimensional feature-space for representing the data, based on a formal definition of functional similarity, is derived. Quantitative validation of the model and the estimation algorithms is provided with a simulation study. Using a real fMRI study for mental arithmetic, the ability of this neurophysiologically inspired model to represent the spatio-temporal information corresponding to mental processes is demonstrated. Moreover, by comparing the models across multiple subjects, natural patterns in mental processes organized according to different mental abilities are revealed. Copyright © 2011 Elsevier Inc. All rights reserved.

Biomedical Applications of Sodium MRI In Vivo

PubMed Central

Madelin, Guillaume; Regatte, Ravinder R.

2013-01-01

In this article, we present an up-to-date overview of the potential biomedical applications of sodium MRI in vivo. Sodium MRI is a subject of increasing interest in translational imaging research as it can give some direct and quantitative biochemical information on the tissue viability, cell integrity and function, and therefore not only help the diagnosis but also the prognosis of diseases and treatment outcomes. It has already been applied in vivo in most of human tissues, such as brain for stroke or tumor detection and therapeutic response, in breast cancer, in articular cartilage, in muscle and in kidney, and it was shown in some studies that it could provide very useful new information not available through standard proton MRI. However, this technique is still very challenging due to the low detectable sodium signal in biological tissue with MRI and hardware/software limitations of the clinical scanners. The article is divided in three parts: (1) the role of sodium in biological tissues, (2) a short review on sodium magnetic resonance, and (3) a review of some studies on sodium MRI on different organs/diseases to date. PMID:23722972

Computer-Aided Detection of Prostate Cancer with MRI: Technology and Applications

PubMed Central

Liu, Lizhi; Tian, Zhiqiang; Zhang, Zhenfeng; Fei, Baowei

2016-01-01

One in six men will develop prostate cancer in his life time. Early detection and accurate diagnosis of the disease can improve cancer survival and reduce treatment costs. Recently, imaging of prostate cancer has greatly advanced since the introduction of multi-parametric magnetic resonance imaging (mp-MRI). Mp-MRI consists of T2-weighted sequences combined with functional sequences including dynamic contrast-enhanced MRI, diffusion-weighted MRI, and MR spectroscopy imaging. Due to the big data and variations in imaging sequences, detection can be affected by multiple factors such as observer variability and visibility and complexity of the lesions. In order to improve quantitative assessment of the disease, various computer-aided detection systems have been designed to help radiologists in their clinical practice. This review paper presents an overview of literatures on computer-aided detection of prostate cancer with mp-MRI, which include the technology and its applications. The aim of the survey is threefold: an introduction for those new to the field, an overview for those working in the field, and a reference for those searching for literature on a specific application. PMID:27133005

Alteration of brain activation patterns in nonallergic rhinitis patients using functional magnetic resonance imaging before and after treatment with intranasal azelastine.

PubMed

Bernstein, Jonathan A; Hastings, Lloyd; Boespflug, Erin L; Allendorfer, Jane B; Lamy, Martine; Eliassen, James C

2011-06-01

Although nonallergic rhinitis (NAR) patients tend to be more sensitive to chemical/olfactory stimuli, a suprathreshold olfactory response or the presence of specific olfactory receptor genes do not explain why their symptoms are triggered by such exposures. To investigate differential neurogenic responses to azelastine in NAR patients, using functional magnetic resonance imaging (fMRI) in response to specific olfactory triggers. A longitudinal study design on 12 subjects with a physician diagnosis of NAR previously demonstrated to be clinically responsive to intranasal azelastine (Astelin) was performed. Subjects underwent fMRI during exposure to unpleasant (hickory smoke) and pleasant (vanilla) odorants while off and then on azelastine for 2 weeks. The olfactory fMRI paradigm consisted of a visually triggered sniff every 21 seconds with synchronized delivery of a 4 second pulse of odorant. Each odorant was presented 18 times over 4-6-minute fMRI runs. Continuous fresh air was presented to wash out each odorant after presentation. Nonallergic rhinitis patients exhibited increased blood flow to several regions of the brain in response to both pleasant and unpleasant odorants, specifically in odor-sensitive regions, while off intranasal azelastine. Treatment with intranasal azelastine significantly attenuated blood flow to regions of the brain relevant to either olfactory sensation or sensory processing in response to these odorants compared with fresh air. The general reduction compared with increase in brain activation in NAR patients on versus off azelastine suggests that a possible effect of this medication may be reduction of brain responses to odorants. Copyright © 2011. Published by Elsevier Inc.

In Vivo Performance of a Novel Fluorinated Magnetic Resonance Imaging Agent for Functional Analysis of Bile Acid Transport

PubMed Central

2015-01-01

A novel trifluorinated cholic acid derivative, CA-lys-TFA, was designed and synthesized for use as a tool to measure bile acid transport noninvasively using magnetic resonance imaging (MRI). In the present study, the in vivo performance of CA-lys-TFA for measuring bile acid transport by MRI was investigated in mice. Gallbladder CA-lys-TFA content was quantified using MRI and liquid chromatography/tandem mass spectrometry. Results in wild-type (WT) C57BL/6J mice were compared to those in mice lacking expression of Asbt, the ileal bile acid transporter. 19F signals emanating from the gallbladders of WT mice 7 h after oral gavage with 150 mg/kg CA-lys-TFA were reproducibly detected by MRI. Asbt-deficient mice administered the same dose had undetectable 19F signals by MRI, and gallbladder bile CA-lys-TFA levels were 30-fold lower compared to WT animals. To our knowledge, this represents the first report of in vivo imaging of an orally absorbed drug using 19F MRI. Fluorinated bile acid analogues have potential as tools to measure and detect abnormal bile acid transport by MRI. PMID:24708306

Detecting Brain State Changes via Fiber-Centered Functional Connectivity Analysis

PubMed Central

Li, Xiang; Lim, Chulwoo; Li, Kaiming; Guo, Lei; Liu, Tianming

2013-01-01

Diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) have been widely used to study structural and functional brain connectivity in recent years. A common assumption used in many previous functional brain connectivity studies is the temporal stationarity. However, accumulating literature evidence has suggested that functional brain connectivity is under temporal dynamic changes in different time scales. In this paper, a novel and intuitive approach is proposed to model and detect dynamic changes of functional brain states based on multimodal fMRI/DTI data. The basic idea is that functional connectivity patterns of all fiber-connected cortical voxels are concatenated into a descriptive functional feature vector to represent the brain’s state, and the temporal change points of brain states are decided by detecting the abrupt changes of the functional vector patterns via the sliding window approach. Our extensive experimental results have shown that meaningful brain state change points can be detected in task-based fMRI/DTI, resting state fMRI/DTI, and natural stimulus fMRI/DTI data sets. Particularly, the detected change points of functional brain states in task-based fMRI corresponded well to the external stimulus paradigm administered to the participating subjects, thus partially validating the proposed brain state change detection approach. The work in this paper provides novel perspective on the dynamic behaviors of functional brain connectivity and offers a starting point for future elucidation of the complex patterns of functional brain interactions and dynamics. PMID:22941508

Demonstration of the reproducibility of free-breathing diffusion-weighted MRI and dynamic contrast enhanced MRI in children with solid tumours: a pilot study.

PubMed

Miyazaki, Keiko; Jerome, Neil P; Collins, David J; Orton, Matthew R; d'Arcy, James A; Wallace, Toni; Moreno, Lucas; Pearson, Andrew D J; Marshall, Lynley V; Carceller, Fernando; Leach, Martin O; Zacharoulis, Stergios; Koh, Dow-Mu

2015-09-01

The objectives are to examine the reproducibility of functional MR imaging in children with solid tumours using quantitative parameters derived from diffusion-weighted (DW-) and dynamic contrast enhanced (DCE-) MRI. Patients under 16-years-of age with confirmed diagnosis of solid tumours (n = 17) underwent free-breathing DW-MRI and DCE-MRI on a 1.5 T system, repeated 24 hours later. DW-MRI (6 b-values, 0-1000 sec/mm(2)) enabled monoexponential apparent diffusion coefficient estimation using all (ADC0-1000) and only ≥100 sec/mm(2) (ADC100-1000) b-values. DCE-MRI was used to derive the transfer constant (K(trans)), the efflux constant (kep), the extracellular extravascular volume (ve), and the plasma fraction (vp), using a study cohort arterial input function (AIF) and the extended Tofts model. Initial area under the gadolinium enhancement curve and pre-contrast T1 were also calculated. Percentage coefficients of variation (CV) of all parameters were calculated. The most reproducible cohort parameters were ADC100-1000 (CV = 3.26%), pre-contrast T1 (CV = 6.21%), and K(trans) (CV = 15.23%). The ADC100-1000 was more reproducible than ADC0-1000, especially extracranially (CV = 2.40% vs. 2.78%). The AIF (n = 9) derived from this paediatric population exhibited sharper and earlier first-pass and recirculation peaks compared with the literature's adult population average. Free-breathing functional imaging protocols including DW-MRI and DCE-MRI are well-tolerated in children aged 6 - 15 with good to moderate measurement reproducibility. • Diffusion MRI protocol is feasible and well-tolerated in a paediatric oncology population. • DCE-MRI for pharmacokinetic evaluation is feasible and well tolerated in a paediatric oncology population. • Paediatric arterial input function (AIF) shows systematic differences from the adult population-average AIF. • Variation of quantitative parameters from paired functional MRI measurements were within 20%.

Single slice US-MRI registration for neurosurgical MRI-guided US

NASA Astrophysics Data System (ADS)

Pardasani, Utsav; Baxter, John S. H.; Peters, Terry M.; Khan, Ali R.

2016-03-01

Image-based ultrasound to magnetic resonance image (US-MRI) registration can be an invaluable tool in image-guided neuronavigation systems. State-of-the-art commercial and research systems utilize image-based registration to assist in functions such as brain-shift correction, image fusion, and probe calibration. Since traditional US-MRI registration techniques use reconstructed US volumes or a series of tracked US slices, the functionality of this approach can be compromised by the limitations of optical or magnetic tracking systems in the neurosurgical operating room. These drawbacks include ergonomic issues, line-of-sight/magnetic interference, and maintenance of the sterile field. For those seeking a US vendor-agnostic system, these issues are compounded with the challenge of instrumenting the probe without permanent modification and calibrating the probe face to the tracking tool. To address these challenges, this paper explores the feasibility of a real-time US-MRI volume registration in a small virtual craniotomy site using a single slice. We employ the Linear Correlation of Linear Combination (LC2) similarity metric in its patch-based form on data from MNI's Brain Images for Tumour Evaluation (BITE) dataset as a PyCUDA enabled Python module in Slicer. By retaining the original orientation information, we are able to improve on the poses using this approach. To further assist the challenge of US-MRI registration, we also present the BOXLC2 metric which demonstrates a speed improvement to LC2, while retaining a similar accuracy in this context.

7 Tesla compatible in-bore display for functional magnetic resonance imaging.

PubMed

Groebner, Jens; Berger, Moritz Cornelius; Umathum, Reiner; Bock, Michael; Rauschenberg, Jaane

2013-08-01

A liquid crystal display was modified for use inside a 7 T MR magnet. SNR measurements were performed using different imaging sequences with the monitor absent, present, or activated. fMRI with a volunteer was conducted using a visual stimulus. SNR was reduced by 3.7%/7.9% in echo planar/fast-spin echo images when the monitor was on which can be explained by the limited shielding of the coated front window (40 dB). In the fMRI experiments, activated regions in the visual cortex were clearly visible. The monitor provided excellent resolution at minor SNR reduction in EPI images, and is thus suitable for fMRI at ultra-high field.

Calibrated LCD/TFT stimulus presentation for visual psychophysics in fMRI.

PubMed

Strasburger, H; Wüstenberg, T; Jäncke, L

2002-11-15

Standard projection techniques using liquid crystal (LCD) or thin-film transistor (TFT) technology show drastic distortions in luminance and contrast characteristics across the screen and across grey levels. Common luminance measurement and calibration techniques are not applicable in the vicinity of MRI scanners. With the aid of a fibre optic, we measured screen luminances for the full space of screen position and image grey values and on that basis developed a compensation technique that involves both luminance homogenisation and position-dependent gamma correction. By the technique described, images displayed to a subject in functional MRI can be specified with high precision by a matrix of desired luminance values rather than by local grey value.

Visual analysis of variance: a tool for quantitative assessment of fMRI data processing and analysis.

PubMed

McNamee, R L; Eddy, W F

2001-12-01

Analysis of variance (ANOVA) is widely used for the study of experimental data. Here, the reach of this tool is extended to cover the preprocessing of functional magnetic resonance imaging (fMRI) data. This technique, termed visual ANOVA (VANOVA), provides both numerical and pictorial information to aid the user in understanding the effects of various parts of the data analysis. Unlike a formal ANOVA, this method does not depend on the mathematics of orthogonal projections or strictly additive decompositions. An illustrative example is presented and the application of the method to a large number of fMRI experiments is discussed. Copyright 2001 Wiley-Liss, Inc.

Partial segmental thrombosis of the corpus cavernosum presenting with perineal pain.

PubMed

Christodoulidou, Michelle; Parnham, Arie; Ramachandran, Navin; Muneer, Asif

2016-11-22

We describe the case of a man aged 43 years who presented with a 2-week history of a palpable lump in the right proximal penile shaft. This was preceded by a 6-month history of perineal pain, accompanied by erectile dysfunction. An urgent MRI scan of his penis identified a thrombus within the right crus and corpus of the penis. His thrombophilia screen was normal. The patient was started on oral anticoagulation and a phosphodiesterase inhibitor (PDE-5i) to prevent thrombus progression and maintain erectile function. At 5 months, the patients' symptoms had resolved and an MRI showed a reduction in the thrombus size. MRI is a useful imaging modality to diagnose a thrombus within the corpus cavernosum in patients presenting with a history of penile and perineal pain together with a palpable lump. The non-enhancement of the lesion helps to differentiate this from alternative rare lesions within the penis and perineum. 2016 BMJ Publishing Group Ltd.

Feature-space-based FMRI analysis using the optimal linear transformation.

PubMed

Sun, Fengrong; Morris, Drew; Lee, Wayne; Taylor, Margot J; Mills, Travis; Babyn, Paul S

2010-09-01

The optimal linear transformation (OLT), an image analysis technique of feature space, was first presented in the field of MRI. This paper proposes a method of extending OLT from MRI to functional MRI (fMRI) to improve the activation-detection performance over conventional approaches of fMRI analysis. In this method, first, ideal hemodynamic response time series for different stimuli were generated by convolving the theoretical hemodynamic response model with the stimulus timing. Second, constructing hypothetical signature vectors for different activity patterns of interest by virtue of the ideal hemodynamic responses, OLT was used to extract features of fMRI data. The resultant feature space had particular geometric clustering properties. It was then classified into different groups, each pertaining to an activity pattern of interest; the applied signature vector for each group was obtained by averaging. Third, using the applied signature vectors, OLT was applied again to generate fMRI composite images with high SNRs for the desired activity patterns. Simulations and a blocked fMRI experiment were employed for the method to be verified and compared with the general linear model (GLM)-based analysis. The simulation studies and the experimental results indicated the superiority of the proposed method over the GLM-based analysis in detecting brain activities.

Functional connectivity and microstructural white matter changes in phenocopy frontotemporal dementia.

PubMed

Meijboom, R; Steketee, R M E; de Koning, I; Osse, R J; Jiskoot, L C; de Jong, F J; van der Lugt, A; van Swieten, J C; Smits, M

2017-04-01

Phenocopy frontotemporal dementia (phFTD) is a rare and poorly understood clinical syndrome. PhFTD shows core behavioural variant FTD (bvFTD) symptoms without associated cognitive deficits and brain abnormalities on conventional MRI and without progression. In contrast to phFTD, functional connectivity and white matter (WM) microstructural abnormalities have been observed in bvFTD. We hypothesise that phFTD belongs to the same disease spectrum as bvFTD and investigated whether functional connectivity and microstructural WM changes similar to bvFTD are present in phFTD. Seven phFTD patients without progression or alternative psychiatric diagnosis, 12 bvFTD patients and 17 controls underwent resting state functional MRI (rs-fMRI) and diffusion tensor imaging (DTI). Default mode network (DMN) connectivity and WM measures were compared between groups. PhFTD showed subtly increased DMN connectivity and subtle microstructural changes in frontal WM tracts. BvFTD showed abnormalities in similar regions as phFTD, but had lower increased DMN connectivity and more extensive microstructural WM changes. Our findings can be interpreted as neuropathological changes in phFTD and are in support of the hypothesis that phFTD and bvFTD may belong to the same disease spectrum. Advanced MRI techniques, objectively identifying brain abnormalities, would therefore be potentially suited to improve the diagnosis of phFTD. • PhFTD shows brain abnormalities that are similar to bvFTD. • PhFTD shows increased functional connectivity in the parietal default mode network. • PhFTD shows microstructural white matter abnormalities in the frontal lobe. • We hypothesise phFTD and bvFTD may belong to the same disease spectrum.

Resting-State Functional Connectivity in the Infant Brain: Methods, Pitfalls, and Potentiality.

PubMed

Mongerson, Chandler R L; Jennings, Russell W; Borsook, David; Becerra, Lino; Bajic, Dusica

2017-01-01

Early brain development is characterized by rapid growth and perpetual reconfiguration, driven by a dynamic milieu of heterogeneous processes. Postnatal brain plasticity is associated with increased vulnerability to environmental stimuli. However, little is known regarding the ontogeny and temporal manifestations of inter- and intra-regional functional connectivity that comprise functional brain networks. Resting-state functional magnetic resonance imaging (rs-fMRI) has emerged as a promising non-invasive neuroinvestigative tool, measuring spontaneous fluctuations in blood oxygen level dependent (BOLD) signal at rest that reflect baseline neuronal activity. Over the past decade, its application has expanded to infant populations providing unprecedented insight into functional organization of the developing brain, as well as early biomarkers of abnormal states. However, many methodological issues of rs-fMRI analysis need to be resolved prior to standardization of the technique to infant populations. As a primary goal, this methodological manuscript will (1) present a robust methodological protocol to extract and assess resting-state networks in early infancy using independent component analysis (ICA), such that investigators without previous knowledge in the field can implement the analysis and reliably obtain viable results consistent with previous literature; (2) review the current methodological challenges and ethical considerations associated with emerging field of infant rs-fMRI analysis; and (3) discuss the significance of rs-fMRI application in infants for future investigations of neurodevelopment in the context of early life stressors and pathological processes. The overarching goal is to catalyze efforts toward development of robust, infant-specific acquisition, and preprocessing pipelines, as well as promote greater transparency by researchers regarding methods used.

Resting-State Functional Connectivity in the Infant Brain: Methods, Pitfalls, and Potentiality

PubMed Central

Mongerson, Chandler R. L.; Jennings, Russell W.; Borsook, David; Becerra, Lino; Bajic, Dusica

2017-01-01

Early brain development is characterized by rapid growth and perpetual reconfiguration, driven by a dynamic milieu of heterogeneous processes. Postnatal brain plasticity is associated with increased vulnerability to environmental stimuli. However, little is known regarding the ontogeny and temporal manifestations of inter- and intra-regional functional connectivity that comprise functional brain networks. Resting-state functional magnetic resonance imaging (rs-fMRI) has emerged as a promising non-invasive neuroinvestigative tool, measuring spontaneous fluctuations in blood oxygen level dependent (BOLD) signal at rest that reflect baseline neuronal activity. Over the past decade, its application has expanded to infant populations providing unprecedented insight into functional organization of the developing brain, as well as early biomarkers of abnormal states. However, many methodological issues of rs-fMRI analysis need to be resolved prior to standardization of the technique to infant populations. As a primary goal, this methodological manuscript will (1) present a robust methodological protocol to extract and assess resting-state networks in early infancy using independent component analysis (ICA), such that investigators without previous knowledge in the field can implement the analysis and reliably obtain viable results consistent with previous literature; (2) review the current methodological challenges and ethical considerations associated with emerging field of infant rs-fMRI analysis; and (3) discuss the significance of rs-fMRI application in infants for future investigations of neurodevelopment in the context of early life stressors and pathological processes. The overarching goal is to catalyze efforts toward development of robust, infant-specific acquisition, and preprocessing pipelines, as well as promote greater transparency by researchers regarding methods used. PMID:28856131

A hybrid method for classifying cognitive states from fMRI data.

PubMed

Parida, S; Dehuri, S; Cho, S-B; Cacha, L A; Poznanski, R R

2015-09-01

Functional magnetic resonance imaging (fMRI) makes it possible to detect brain activities in order to elucidate cognitive-states. The complex nature of fMRI data requires under-standing of the analyses applied to produce possible avenues for developing models of cognitive state classification and improving brain activity prediction. While many models of classification task of fMRI data analysis have been developed, in this paper, we present a novel hybrid technique through combining the best attributes of genetic algorithms (GAs) and ensemble decision tree technique that consistently outperforms all other methods which are being used for cognitive-state classification. Specifically, this paper illustrates the combined effort of decision-trees ensemble and GAs for feature selection through an extensive simulation study and discusses the classification performance with respect to fMRI data. We have shown that our proposed method exhibits significant reduction of the number of features with clear edge classification accuracy over ensemble of decision-trees.

Visual analytics of brain networks.

PubMed

Li, Kaiming; Guo, Lei; Faraco, Carlos; Zhu, Dajiang; Chen, Hanbo; Yuan, Yixuan; Lv, Jinglei; Deng, Fan; Jiang, Xi; Zhang, Tuo; Hu, Xintao; Zhang, Degang; Miller, L Stephen; Liu, Tianming

2012-05-15

Identification of regions of interest (ROIs) is a fundamental issue in brain network construction and analysis. Recent studies demonstrate that multimodal neuroimaging approaches and joint analysis strategies are crucial for accurate, reliable and individualized identification of brain ROIs. In this paper, we present a novel approach of visual analytics and its open-source software for ROI definition and brain network construction. By combining neuroscience knowledge and computational intelligence capabilities, visual analytics can generate accurate, reliable and individualized ROIs for brain networks via joint modeling of multimodal neuroimaging data and an intuitive and real-time visual analytics interface. Furthermore, it can be used as a functional ROI optimization and prediction solution when fMRI data is unavailable or inadequate. We have applied this approach to an operation span working memory fMRI/DTI dataset, a schizophrenia DTI/resting state fMRI (R-fMRI) dataset, and a mild cognitive impairment DTI/R-fMRI dataset, in order to demonstrate the effectiveness of visual analytics. Our experimental results are encouraging. Copyright © 2012 Elsevier Inc. All rights reserved.

Prospect theory does not describe the feedback-related negativity value function.

PubMed

Sambrook, Thomas D; Roser, Matthew; Goslin, Jeremy

2012-12-01

Humans handle uncertainty poorly. Prospect theory accounts for this with a value function in which possible losses are overweighted compared to possible gains, and the marginal utility of rewards decreases with size. fMRI studies have explored the neural basis of this value function. A separate body of research claims that prediction errors are calculated by midbrain dopamine neurons. We investigated whether the prospect theoretic effects shown in behavioral and fMRI studies were present in midbrain prediction error coding by using the feedback-related negativity, an ERP component believed to reflect midbrain prediction errors. Participants' stated satisfaction with outcomes followed prospect theory but their feedback-related negativity did not, instead showing no effect of marginal utility and greater sensitivity to potential gains than losses. Copyright © 2012 Society for Psychophysiological Research.

Awake Craniotomy with Noninvasive Brain Mapping by 3-Tesla Functional Magnetic Resonance Imaging for Excision of Low-grade Glioma: A Case of a Young Patient from Pakistan.

PubMed

Aleem Bhatti, Atta Ul; Jakhrani, Nasir Khan; Parekh, Maria Adnan

2018-01-01

The past few years have seen increasing support for gross total resection in the management of low-grade gliomas (LGGs), with a greater extent of resection correlated with better overall survival, progression-free survival, and time to malignant transformation. There is consistent evidence in literature supporting extent of safe resection as a good prognostic indicator as well as positively affecting seizure control, symptomatic relief in pressure symptoms, and longer progression-free and total survival. The operative goal in most LGG cases is to maximize the extent of resection for these benefits while avoiding postoperative neurologic deficits. Several advanced invasive and noninvasive surgical techniques such as intraoperative magnetic resonance imaging (MRI), fluorescence-guided surgery, intraoperative functional pathway mapping, and neuronavigation have been developed in an attempt to better achieve maximal safe resection. We present a case of LGG in a young patient with a 5-year history of refractory seizures and gradual onset walking difficulty. Serial MRI brain scans revealed a progressive increase in right frontal tumor size with substantial edema and parafalcine herniation. Noninvasive brain mapping by functional MRI (fMRI) and sleep-awake-sleep type of anesthesia with endotracheal tube insertion was utilized during an awake craniotomy. Histopathology confirmed a Grade II oligodendroglioma, and genetic analysis revealed no codeletion at 1p/19q. Neurological improvement was remarkable in terms of immediate motor improvement, and the patient remained completely seizure free on a single antiepileptic drug. There is no radiologic or clinical evidence of recurrence 6 months postoperatively. This is the first published report of an awake craniotomy for LGG in Pakistan. The contemporary concept of supratotal resection in LGGs advocates generous functional resection even beyond MRI findings rather than mere excision of oncological boundaries. This relatively aggressive approach is only possible with an awake craniotomy, which ensures preservation of functional status and thus less postoperative morbidity and better outcomes. Noninvasive mapping for intracranial space-occupying lesions, including fMRI and blood-oxygen-level dependent (BOLD) imaging modality, is an essential tool in a resource-limited setting such as Pakistan.

Active shielding of cylindrical saddle-shaped coils: application to wire-wound RF coils for very low field NMR and MRI.

PubMed

Bidinosti, C P; Kravchuk, I S; Hayden, M E

2005-11-01

We provide an exact expression for the magnetic field produced by cylindrical saddle-shaped coils and their ideal shield currents in the low-frequency limit. The stream function associated with the shield surface current is also determined. The results of the analysis are useful for the design of actively shielded radio-frequency (RF) coils. Examples pertinent to very low field nuclear magnetic resonance (NMR) and magnetic resonance imaging (MRI) are presented and discussed.

Spatially aggregated multiclass pattern classification in functional MRI using optimally selected functional brain areas.

PubMed

Zheng, Weili; Ackley, Elena S; Martínez-Ramón, Manel; Posse, Stefan

2013-02-01

In previous works, boosting aggregation of classifier outputs from discrete brain areas has been demonstrated to reduce dimensionality and improve the robustness and accuracy of functional magnetic resonance imaging (fMRI) classification. However, dimensionality reduction and classification of mixed activation patterns of multiple classes remain challenging. In the present study, the goals were (a) to reduce dimensionality by combining feature reduction at the voxel level and backward elimination of optimally aggregated classifiers at the region level, (b) to compare region selection for spatially aggregated classification using boosting and partial least squares regression methods and (c) to resolve mixed activation patterns using probabilistic prediction of individual tasks. Brain activation maps from interleaved visual, motor, auditory and cognitive tasks were segmented into 144 functional regions. Feature selection reduced the number of feature voxels by more than 50%, leaving 95 regions. The two aggregation approaches further reduced the number of regions to 30, resulting in more than 75% reduction of classification time and misclassification rates of less than 3%. Boosting and partial least squares (PLS) were compared to select the most discriminative and the most task correlated regions, respectively. Successful task prediction in mixed activation patterns was feasible within the first block of task activation in real-time fMRI experiments. This methodology is suitable for sparsifying activation patterns in real-time fMRI and for neurofeedback from distributed networks of brain activation. Copyright © 2013 Elsevier Inc. All rights reserved.

Associations of resting-state fMRI functional connectivity with flow-BOLD coupling and regional vasculature.

PubMed

Tak, Sungho; Polimeni, Jonathan R; Wang, Danny J J; Yan, Lirong; Chen, J Jean

2015-04-01

There has been tremendous interest in applying functional magnetic resonance imaging-based resting-state functional connectivity (rs-fcMRI) measurements to the study of brain function. However, a lack of understanding of the physiological mechanisms of rs-fcMRI limits their ability to interpret rs-fcMRI findings. In this work, the authors examine the regional associations between rs-fcMRI estimates and dynamic coupling between the blood oxygenation level-dependent (BOLD) and cerebral blood flow (CBF), as well as resting macrovascular volume. Resting-state BOLD and CBF data were simultaneously acquired using a dual-echo pseudocontinuous arterial spin labeling (pCASL) technique, whereas macrovascular volume fraction was estimated using time-of-flight MR angiography. Functional connectivity within well-known functional networks—including the default mode, frontoparietal, and primary sensory-motor networks—was calculated using a conventional seed-based correlation approach. They found the functional connectivity strength to be significantly correlated with the regional increase in CBF-BOLD coupling strength and inversely proportional to macrovascular volume fraction. These relationships were consistently observed within all functional networks considered. Their findings suggest that highly connected networks observed using rs-fcMRI are not likely to be mediated by common vascular drainage linking distal cortical areas. Instead, high BOLD functional connectivity is more likely to reflect tighter neurovascular connections, attributable to neuronal pathways.

Intraoperative visualisation of functional structures facilitates safe frameless stereotactic biopsy in the motor eloquent regions of the brain.

PubMed

Zhang, Jia-Shu; Qu, Ling; Wang, Qun; Jin, Wei; Hou, Yuan-Zheng; Sun, Guo-Chen; Li, Fang-Ye; Yu, Xin-Guang; Xu, Ban-Nan; Chen, Xiao-Lei

2017-12-20

For stereotactic brain biopsy involving motor eloquent regions, the surgical objective is to enhance diagnostic yield and preserve neurological function. To achieve this aim, we implemented functional neuro-navigation and intraoperative magnetic resonance imaging (iMRI) into the biopsy procedure. The impact of this integrated technique on the surgical outcome and postoperative neurological function was investigated and evaluated. Thirty nine patients with lesions involving motor eloquent structures underwent frameless stereotactic biopsy assisted by functional neuro-navigation and iMRI. Intraoperative visualisation was realised by integrating anatomical and functional information into a navigation framework to improve biopsy trajectories and preserve eloquent structures. iMRI was conducted to guarantee the biopsy accuracy and detect intraoperative complications. The perioperative change of motor function and biopsy error before and after iMRI were recorded, and the role of functional information in trajectory selection and the relationship between the distance from sampling site to nearby eloquent structures and the neurological deterioration were further analyzed. Functional neuro-navigation helped modify the original trajectories and sampling sites in 35.90% (16/39) of cases to avoid the damage of eloquent structures. Even though all the lesions were high-risk of causing neurological deficits, no significant difference was found between preoperative and postoperative muscle strength. After data analysis, 3mm was supposed to be the safe distance for avoiding transient neurological deterioration. During surgery, the use of iMRI significantly reduced the biopsy errors (p = 0.042) and potentially increased the diagnostic yield from 84.62% (33/39) to 94.87% (37/39). Moreover, iMRI detected intraoperative haemorrhage in 5.13% (2/39) of patients, all of them benefited from the intraoperative strategies based on iMRI findings. Intraoperative visualisation of functional structures could be a feasible, safe and effective technique. Combined with intraoperative high-field MRI, it contributed to enhance the biopsy accuracy and lower neurological complications in stereotactic brain biopsy involving motor eloquent areas.

Development from childhood to adulthood increases morphological and functional inter-individual variability in the right superior temporal cortex.

PubMed

Bonte, Milene; Frost, Martin A; Rutten, Sanne; Ley, Anke; Formisano, Elia; Goebel, Rainer

2013-12-01

We study the developmental trajectory of morphology and function of the superior temporal cortex (STC) in children (8-9 years), adolescents (14-15 years) and young adults. We analyze cortical surface landmarks and functional MRI (fMRI) responses to voices, other natural categories and tones and examine how hemispheric asymmetry and inter-subject variability change across age. Our results show stable morphological asymmetries across age groups, including a larger left planum temporale and a deeper right superior temporal sulcus. fMRI analyses show that a rightward lateralization for voice-selective responses is present in all groups but decreases with age. Furthermore, STC responses to voices change from being less selective and more spatially diffuse in children to highly selective and focal in adults. Interestingly, the analysis of morphological landmarks reveals that inter-subject variability increases during development in the right--but not in the left--STC. Similarly, inter-subject variability of cortically-realigned functional responses to voices, other categories and tones increases with age in the right STC. Our findings reveal asymmetric developmental changes in brain regions crucial for auditory and voice perception. The age-related increase of inter-subject variability in right STC suggests that anatomy and function of this region are shaped by unique individual developmental experiences. © 2013.

Neurovascular coupling in normal aging: a combined optical, ERP and fMRI study.

PubMed

Fabiani, Monica; Gordon, Brian A; Maclin, Edward L; Pearson, Melanie A; Brumback-Peltz, Carrie R; Low, Kathy A; McAuley, Edward; Sutton, Bradley P; Kramer, Arthur F; Gratton, Gabriele

2014-01-15

Brain aging is characterized by changes in both hemodynamic and neuronal responses, which may be influenced by the cardiorespiratory fitness of the individual. To investigate the relationship between neuronal and hemodynamic changes, we studied the brain activity elicited by visual stimulation (checkerboard reversals at different frequencies) in younger adults and in older adults varying in physical fitness. Four functional brain measures were used to compare neuronal and hemodynamic responses obtained from BA17: two reflecting neuronal activity (the event-related optical signal, EROS, and the C1 response of the ERP), and two reflecting functional hemodynamic changes (functional magnetic resonance imaging, fMRI, and near-infrared spectroscopy, NIRS). The results indicated that both younger and older adults exhibited a quadratic relationship between neuronal and hemodynamic effects, with reduced increases of the hemodynamic response at high levels of neuronal activity. Although older adults showed reduced activation, similar neurovascular coupling functions were observed in the two age groups when fMRI and deoxy-hemoglobin measures were used. However, the coupling between oxy- and deoxy-hemoglobin changes decreased with age and increased with increasing fitness. These data indicate that departures from linearity in neurovascular coupling may be present when using hemodynamic measures to study neuronal function. Copyright © 2013 Elsevier Inc. All rights reserved.

Neural Markers and Rehabilitation of Executive Functioning in Veterans with TBI and PTSD

DTIC Science & Technology

2015-10-01

functioning. Functional magnetic resonance imaging ( fMRI ) will be used to evaluate changes in cortical function in frontostriate and frontoparietal circuits...EEG and fMRI will be conducted and then transport Veterans back to our laboratory. We will assure transportation is running efficiently and without...delays before study commencement.  Transportation to the EEG and fMRI was arranged through the UNC-Chapel Hill School of Medicine at month 9

Complementary role of magnetic resonance imaging in the study of the fetal urinary system.

PubMed

Gómez Huertas, M; Culiañez Casas, M; Molina García, F S; Carrillo Badillo, M P; Pastor Pons, E

2016-01-01

Urinary system birth defects represent the abnormality most often detected in prenatal studies, accounting for 30% to 50% of all structural anomalies present at birth. The most common disorders are urinary tract dilation, developmental variants, cystic kidney diseases, kidney tumors, and bladder defects. These anomalies can present in isolation or in association with various syndromes. They are normally evaluated with sonography, and the use of magnetic resonance imaging (MRI) is considered only in inconclusive cases. In this article, we show the potential of fetal MRI as a technique to complement sonography in the study of fetal urinary system anomalies. We show the additional information that MRI can provide in each entity, especially in the evaluation of kidney function through diffusion-weighted sequences. Copyright © 2016 SERAM. Published by Elsevier España, S.L.U. All rights reserved.

Resting-State Functional Connectivity-Based Biomarkers and Functional MRI-Based Neurofeedback for Psychiatric Disorders: A Challenge for Developing Theranostic Biomarkers.

PubMed

Yamada, Takashi; Hashimoto, Ryu-Ichiro; Yahata, Noriaki; Ichikawa, Naho; Yoshihara, Yujiro; Okamoto, Yasumasa; Kato, Nobumasa; Takahashi, Hidehiko; Kawato, Mitsuo

2017-10-01

Psychiatric research has been hampered by an explanatory gap between psychiatric symptoms and their neural underpinnings, which has resulted in poor treatment outcomes. This situation has prompted us to shift from symptom-based diagnosis to data-driven diagnosis, aiming to redefine psychiatric disorders as disorders of neural circuitry. Promising candidates for data-driven diagnosis include resting-state functional connectivity MRI (rs-fcMRI)-based biomarkers. Although biomarkers have been developed with the aim of diagnosing patients and predicting the efficacy of therapy, the focus has shifted to the identification of biomarkers that represent therapeutic targets, which would allow for more personalized treatment approaches. This type of biomarker (i.e., "theranostic biomarker") is expected to elucidate the disease mechanism of psychiatric conditions and to offer an individualized neural circuit-based therapeutic target based on the neural cause of a condition. To this end, researchers have developed rs-fcMRI-based biomarkers and investigated a causal relationship between potential biomarkers and disease-specific behavior using functional MRI (fMRI)-based neurofeedback on functional connectivity. In this review, we introduce a recent approach for creating a theranostic biomarker, which consists mainly of 2 parts: (1) developing an rs-fcMRI-based biomarker that can predict diagnosis and/or symptoms with high accuracy, and (2) the introduction of a proof-of-concept study investigating the relationship between normalizing the biomarker and symptom changes using fMRI-based neurofeedback. In parallel with the introduction of recent studies, we review rs-fcMRI-based biomarker and fMRI-based neurofeedback, focusing on the technological improvements and limitations associated with clinical use. © The Author 2017. Published by Oxford University Press on behalf of CINP.

Resting-State Functional Connectivity-Based Biomarkers and Functional MRI-Based Neurofeedback for Psychiatric Disorders: A Challenge for Developing Theranostic Biomarkers

PubMed Central

Yamada, Takashi; Hashimoto, Ryu-ichiro; Yahata, Noriaki; Ichikawa, Naho; Yoshihara, Yujiro; Okamoto, Yasumasa; Kato, Nobumasa; Takahashi, Hidehiko

2017-01-01

Abstract Psychiatric research has been hampered by an explanatory gap between psychiatric symptoms and their neural underpinnings, which has resulted in poor treatment outcomes. This situation has prompted us to shift from symptom-based diagnosis to data-driven diagnosis, aiming to redefine psychiatric disorders as disorders of neural circuitry. Promising candidates for data-driven diagnosis include resting-state functional connectivity MRI (rs-fcMRI)-based biomarkers. Although biomarkers have been developed with the aim of diagnosing patients and predicting the efficacy of therapy, the focus has shifted to the identification of biomarkers that represent therapeutic targets, which would allow for more personalized treatment approaches. This type of biomarker (i.e., “theranostic biomarker”) is expected to elucidate the disease mechanism of psychiatric conditions and to offer an individualized neural circuit-based therapeutic target based on the neural cause of a condition. To this end, researchers have developed rs-fcMRI-based biomarkers and investigated a causal relationship between potential biomarkers and disease-specific behavior using functional MRI (fMRI)-based neurofeedback on functional connectivity. In this review, we introduce a recent approach for creating a theranostic biomarker, which consists mainly of 2 parts: (1) developing an rs-fcMRI-based biomarker that can predict diagnosis and/or symptoms with high accuracy, and (2) the introduction of a proof-of-concept study investigating the relationship between normalizing the biomarker and symptom changes using fMRI-based neurofeedback. In parallel with the introduction of recent studies, we review rs-fcMRI-based biomarker and fMRI-based neurofeedback, focusing on the technological improvements and limitations associated with clinical use. PMID:28977523

Neural Activation to Emotional Faces in Adolescents with Autism Spectrum Disorders

ERIC Educational Resources Information Center

Weng, Shih-Jen; Carrasco, Melisa; Swartz, Johnna R.; Wiggins, Jillian Lee; Kurapati, Nikhil; Liberzon, Israel; Risi, Susan; Lord, Catherine; Monk, Christopher S.

2011-01-01

Background: Autism spectrum disorders (ASD) involve a core deficit in social functioning and impairments in the ability to recognize face emotions. In an emotional faces task designed to constrain group differences in attention, the present study used functional MRI to characterize activation in the amygdala, ventral prefrontal cortex (vPFC), and…

Individual Differences in the Alignment of Structural and Functional Markers of the V5/MT Complex in Primates

PubMed Central

Large, I.; Bridge, H.; Ahmed, B.; Clare, S.; Kolasinski, J.; Lam, W. W.; Miller, K. L.; Dyrby, T. B.; Parker, A. J.; Smith, J. E. T.; Daubney, G.; Sallet, J.; Bell, A. H.; Krug, K.

2016-01-01

Extrastriate visual area V5/MT in primates is defined both structurally by myeloarchitecture and functionally by distinct responses to visual motion. Myelination is directly identifiable from postmortem histology but also indirectly by image contrast with structural magnetic resonance imaging (sMRI). First, we compared the identification of V5/MT using both sMRI and histology in Rhesus macaques. A section-by-section comparison of histological slices with in vivo and postmortem sMRI for the same block of cortical tissue showed precise correspondence in localizing heavy myelination for V5/MT and neighboring MST. Thus, sMRI in macaques accurately locates histologically defined myelin within areas known to be motion selective. Second, we investigated the functionally homologous human motion complex (hMT+) using high-resolution in vivo imaging. Humans showed considerable intersubject variability in hMT+ location, when defined with myelin-weighted sMRI signals to reveal structure. When comparing sMRI markers to functional MRI in response to moving stimuli, a region of high myelin signal was generally located within the hMT+ complex. However, there were considerable differences in the alignment of structural and functional markers between individuals. Our results suggest that variation in area identification for hMT+ based on structural and functional markers reflects individual differences in human regional brain architecture. PMID:27371764

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

Stancanello, Joseph; Cavedon, Carlo; Francescon, Paolo

Functional magnetic resonance imaging (fMRI) is used to distinguish areas of the brain responsible for different tasks and functions. It is possible, for example, by using fMRI images, to identify particular regions in the brain which can be considered as 'functional organs at risk' (fOARs), i.e., regions which would cause significant patient morbidity if compromised. The aim of this study is to propose and validate a method to exploit functional information for the identification of fOARs in CyberKnife (Accuray, Inc., Sunnyvale, CA) radiosurgery treatment planning; in particular, given the high spatial accuracy offered by the CyberKnife system, local nonrigid registrationmore » is used to reach accurate image matching. Five patients affected by arteriovenous malformations (AVMs) and scheduled to undergo radiosurgery were scanned prior to treatment using computed tomography (CT), three-dimensional (3D) rotational angiography (3DRA), T2 weighted and blood oxygenation level dependent echo planar imaging MRI. Tasks were chosen on the basis of lesion location by considering those areas which could be potentially close to treatment targets. Functional data were superimposed on 3DRA and CT used for treatment planning. The procedure for the localization of fMRI areas was validated by direct cortical stimulation on 38 AVM and tumor patients undergoing conventional surgery. Treatment plans studied with and without considering fOARs were significantly different, in particular with respect to both maximum dose and dose volume histograms; consideration of the fOARs allowed quality indices of treatment plans to remain almost constant or to improve in four out of five cases compared to plans with no consideration of fOARs. In conclusion, the presented method provides an accurate tool for the integration of functional information into AVM radiosurgery, which might help to minimize undesirable side effects and to make radiosurgery less invasive.« less

A feature-based approach to combine functional MRI, structural MRI and EEG brain imaging data.

PubMed

Calhoun, V; Adali, T; Liu, J

2006-01-01

The acquisition of multiple brain imaging types for a given study is a very common practice. However these data are typically examined in separate analyses, rather than in a combined model. We propose a novel methodology to perform joint independent component analysis across image modalities, including structural MRI data, functional MRI activation data and EEG data, and to visualize the results via a joint histogram visualization technique. Evaluation of which combination of fused data is most useful is determined by using the Kullback-Leibler divergence. We demonstrate our method on a data set composed of functional MRI data from two tasks, structural MRI data, and EEG data collected on patients with schizophrenia and healthy controls. We show that combining data types can improve our ability to distinguish differences between groups.

Prediction of individual brain maturity using fMRI.

PubMed

Dosenbach, Nico U F; Nardos, Binyam; Cohen, Alexander L; Fair, Damien A; Power, Jonathan D; Church, Jessica A; Nelson, Steven M; Wig, Gagan S; Vogel, Alecia C; Lessov-Schlaggar, Christina N; Barnes, Kelly Anne; Dubis, Joseph W; Feczko, Eric; Coalson, Rebecca S; Pruett, John R; Barch, Deanna M; Petersen, Steven E; Schlaggar, Bradley L

2010-09-10

Group functional connectivity magnetic resonance imaging (fcMRI) studies have documented reliable changes in human functional brain maturity over development. Here we show that support vector machine-based multivariate pattern analysis extracts sufficient information from fcMRI data to make accurate predictions about individuals' brain maturity across development. The use of only 5 minutes of resting-state fcMRI data from 238 scans of typically developing volunteers (ages 7 to 30 years) allowed prediction of individual brain maturity as a functional connectivity maturation index. The resultant functional maturation curve accounted for 55% of the sample variance and followed a nonlinear asymptotic growth curve shape. The greatest relative contribution to predicting individual brain maturity was made by the weakening of short-range functional connections between the adult brain's major functional networks.

[Introduction of neuroethics: out of clinic, beyond academia in human brain research].

PubMed

Fukushi, Tamami; Sakura, Osamu

2008-11-01

Higher cognitive function in human brain is one of well-developed fields of neuroscience research in the 21st century. Especially functional magnetic resonance imaging (fMRI) and near infrared recording system have brought so many non-clinical researchers whose background is such as cognitive psychology, economics, politics, pedagogy, and so on, to the human brain mapping study. Authors have introduced the ethical issues related to incidental findings during the fMRI recording for non-clinical purpose, which is a typical problem derived from such expanded human brain research under non clinical condition, that is, neuroethics. In the present article we would introduce neuroethical issues in contexts of "out of clinic" and "beyond academia".

Automated Real-Time Behavioral and Physiological Data Acquisition and Display Integrated with Stimulus Presentation for fMRI

PubMed Central

Voyvodic, James T.; Glover, Gary H.; Greve, Douglas; Gadde, Syam

2011-01-01

Functional magnetic resonance imaging (fMRI) is based on correlating blood oxygen-level dependent (BOLD) signal fluctuations in the brain with other time-varying signals. Although the most common reference for correlation is the timing of a behavioral task performed during the scan, many other behavioral and physiological variables can also influence fMRI signals. Variations in cardiac and respiratory functions in particular are known to contribute significant BOLD signal fluctuations. Variables such as skin conduction, eye movements, and other measures that may be relevant to task performance can also be correlated with BOLD signals and can therefore be used in image analysis to differentiate multiple components in complex brain activity signals. Combining real-time recording and data management of multiple behavioral and physiological signals in a way that can be routinely used with any task stimulus paradigm is a non-trivial software design problem. Here we discuss software methods that allow users control of paradigm-specific audio–visual or other task stimuli combined with automated simultaneous recording of multi-channel behavioral and physiological response variables, all synchronized with sub-millisecond temporal accuracy. We also discuss the implementation and importance of real-time display feedback to ensure data quality of all recorded variables. Finally, we discuss standards and formats for storage of temporal covariate data and its integration into fMRI image analysis. These neuroinformatics methods have been adopted for behavioral task control at all sites in the Functional Biomedical Informatics Research Network (FBIRN) multi-center fMRI study. PMID:22232596

Long-term recovery of motor function in a quadriplegic patient with diffuse axonal injury and traumatic hemorrhage: a case report.

PubMed

Kim, Dong Gyu; Kim, Seong Ho; Kim, Oh Lyong; Cho, Yun Woo; Son, Su Min; Jang, Sung Ho

2009-01-01

There have been no studies on motor recovery in severe quadriplegic patients with traumatic brain injury (TBI) resulting from combined causes of weakness; this type of patient is often seen in rehabilitation clinics. We report on a quadriplegic patient who showed long-term motor recovery from severe weakness caused by a diffuse axonal injury (DAI) on the brainstem and a traumatic intracerebral hemorrhage (ICH) on left cerebral peduncle, as evaluated by diffuse tensor imaging (DTI) and functional MRI (fMRI). A 17-year-old male patient presented with quadriparesis at the onset of TBI. Over the 28-month period following the onset of the injury, the motor function of the four extremities slowly recovered to a range that was nearly normal. Two longitudinal DTIs (at 11 and 28 months from onset) and fMRI (at 28 months) were performed. Fractional anisotropy and an apparent diffusion coefficient were measured using the region of interest method, and diffusion tensor tractography was conducted using a DTI/fMRI combination. Fractional anisotrophy values in the brainstem, which were markedly decreased on the 11-month DTI, were increased on the 28-month DTI. On the fMRI performed at 28 months, the contralateral primary sensori-motor cortex was activated by the movement of either the right or left hand. Diffusion tensor tractography showed that fiber tracts originating from the motor-sensory cortex passed through the known corticospinal tract pathway to the pons. It seems that the weakness of this patient recovered due to the recovery of the damaged corticospinal tracts.

Function Biomedical Informatics Research Network Recommendations for Prospective Multi-Center Functional Magnetic Resonance Imaging Studies

PubMed Central

Glover, Gary H.; Mueller, Bryon A.; Turner, Jessica A.; van Erp, Theo G.M.; Liu, Thomas T.; Greve, Douglas N.; Voyvodic, James T.; Rasmussen, Jerod; Brown, Gregory G.; Keator, David B.; Calhoun, Vince D.; Lee, Hyo Jong; Ford, Judith M.; Mathalon, Daniel H.; Diaz, Michele; O’Leary, Daniel S.; Gadde, Syam; Preda, Adrian; Lim, Kelvin O.; Wible, Cynthia G.; Stern, Hal S.; Belger, Aysenil; McCarthy, Gregory; Ozyurt, Burak; Potkin, Steven G.

2011-01-01

This report provides practical recommendations for the design and execution of Multi-Center functional Magnetic Resonance Imaging (MC-fMRI) studies based on the collective experience of the Function Biomedical Informatics Research Network (FBIRN). The paper was inspired by many requests from the fMRI community to FBIRN group members for advice on how to conduct MC-fMRI studies. The introduction briefly discusses the advantages and complexities of MC-fMRI studies. Prerequisites for MC-fMRI studies are addressed before delving into the practical aspects of carefully and efficiently setting up a MC-fMRI study. Practical multi-site aspects include: (1) establishing and verifying scan parameters including scanner types and magnetic fields, (2) establishing and monitoring of a scanner quality program, (3) developing task paradigms and scan session documentation, (4) establishing clinical and scanner training to ensure consistency over time, (5) developing means for uploading, storing, and monitoring of imaging and other data, (6) the use of a traveling fMRI expert and (7) collectively analyzing imaging data and disseminating results. We conclude that when MC-fMRI studies are organized well with careful attention to unification of hardware, software and procedural aspects, the process can be a highly effective means for accessing a desired participant demographics while accelerating scientific discovery. PMID:22314879

Functional magnetic resonance imaging.

PubMed

Buchbinder, Bradley R

2016-01-01

Functional magnetic resonance imaging (fMRI) maps the spatiotemporal distribution of neural activity in the brain under varying cognitive conditions. Since its inception in 1991, blood oxygen level-dependent (BOLD) fMRI has rapidly become a vital methodology in basic and applied neuroscience research. In the clinical realm, it has become an established tool for presurgical functional brain mapping. This chapter has three principal aims. First, we review key physiologic, biophysical, and methodologic principles that underlie BOLD fMRI, regardless of its particular area of application. These principles inform a nuanced interpretation of the BOLD fMRI signal, along with its neurophysiologic significance and pitfalls. Second, we illustrate the clinical application of task-based fMRI to presurgical motor, language, and memory mapping in patients with lesions near eloquent brain areas. Integration of BOLD fMRI and diffusion tensor white-matter tractography provides a road map for presurgical planning and intraoperative navigation that helps to maximize the extent of lesion resection while minimizing the risk of postoperative neurologic deficits. Finally, we highlight several basic principles of resting-state fMRI and its emerging translational clinical applications. Resting-state fMRI represents an important paradigm shift, focusing attention on functional connectivity within intrinsic cognitive networks. © 2016 Elsevier B.V. All rights reserved.

Structural and functional correlates of visual field asymmetry in the human brain by diffusion kurtosis MRI and functional MRI.

PubMed

O'Connell, Caitlin; Ho, Leon C; Murphy, Matthew C; Conner, Ian P; Wollstein, Gadi; Cham, Rakie; Chan, Kevin C

2016-11-09

Human visual performance has been observed to show superiority in localized regions of the visual field across many classes of stimuli. However, the underlying neural mechanisms remain unclear. This study aims to determine whether the visual information processing in the human brain is dependent on the location of stimuli in the visual field and the corresponding neuroarchitecture using blood-oxygenation-level-dependent functional MRI (fMRI) and diffusion kurtosis MRI, respectively, in 15 healthy individuals at 3 T. In fMRI, visual stimulation to the lower hemifield showed stronger brain responses and larger brain activation volumes than the upper hemifield, indicative of the differential sensitivity of the human brain across the visual field. In diffusion kurtosis MRI, the brain regions mapping to the lower visual field showed higher mean kurtosis, but not fractional anisotropy or mean diffusivity compared with the upper visual field. These results suggested the different distributions of microstructural organization across visual field brain representations. There was also a strong positive relationship between diffusion kurtosis and fMRI responses in the lower field brain representations. In summary, this study suggested the structural and functional brain involvements in the asymmetry of visual field responses in humans, and is important to the neurophysiological and psychological understanding of human visual information processing.

Comparison of block and event-related experimental designs in diffusion-weighted functional MRI.

PubMed

Williams, Rebecca J; McMahon, Katie L; Hocking, Julia; Reutens, David C

2014-08-01

To compare diffusion-weighted functional magnetic resonance imaging (DfMRI), a novel alternative to the blood oxygenation level-dependent (BOLD) contrast, in a functional MRI experiment. Nine participants viewed contrast reversing (7.5 Hz) black-and-white checkerboard stimuli using block and event-related paradigms. DfMRI (b = 1800 mm/s(2)) and BOLD sequences were acquired. Four parameters describing the observed signal were assessed: percent signal change, spatial extent of the activation, the Euclidean distance between peak voxel locations, and the time-to-peak of the best fitting impulse response for different paradigms and sequences. The BOLD conditions showed a higher percent signal change relative to DfMRI; however, event-related DfMRI showed the strongest group activation (t = 21.23, P < 0.0005). Activation was more diffuse and spatially closer to the BOLD response for DfMRI when the block design was used. DfMRIevent showed the shortest TTP (4.4 ± 0.88 sec). The hemodynamic contribution to DfMRI may increase with the use of block designs. © 2013 Wiley Periodicals, Inc.

Neuroimaging of love: fMRI meta-analysis evidence toward new perspectives in sexual medicine.

PubMed

Ortigue, Stephanie; Bianchi-Demicheli, Francesco; Patel, Nisa; Frum, Chris; Lewis, James W

2010-11-01

Brain imaging is becoming a powerful tool in the study of human cerebral functions related to close personal relationships. Outside of subcortical structures traditionally thought to be involved in reward-related systems, a wide range of neuroimaging studies in relationship science indicate a prominent role for different cortical networks and cognitive factors. Thus, the field needs a better anatomical/network/whole-brain model to help translate scientific knowledge from lab bench to clinical models and ultimately to the patients suffering from disorders associated with love and couple relationships. The aim of the present review is to provide a review across wide range of functional magnetic resonance imaging (fMRI) studies to critically identify the cortical networks associated with passionate love, and to compare and contrast it with other types of love (such as maternal love and unconditional love for persons with intellectual disabilities). Retrospective review of pertinent neuroimaging literature. Review of published literature on fMRI studies of love illustrating brain regions associated with different forms of love. Although all fMRI studies of love point to the subcortical dopaminergic reward-related brain systems (involving dopamine and oxytocin receptors) for motivating individuals in pair-bonding, the present meta-analysis newly demonstrated that different types of love involve distinct cerebral networks, including those for higher cognitive functions such as social cognition and bodily self-representation. These metaresults provide the first stages of a global neuroanatomical model of cortical networks involved in emotions related to different aspects of love. Developing this model in future studies should be helpful for advancing clinical approaches helpful in sexual medicine and couple therapy. © 2010 International Society for Sexual Medicine.

Identifying Rodent Resting-State Brain Networks with Independent Component Analysis

PubMed Central

Bajic, Dusica; Craig, Michael M.; Mongerson, Chandler R. L.; Borsook, David; Becerra, Lino

2017-01-01

Rodent models have opened the door to a better understanding of the neurobiology of brain disorders and increased our ability to evaluate novel treatments. Resting-state functional magnetic resonance imaging (rs-fMRI) allows for in vivo exploration of large-scale brain networks with high spatial resolution. Its application in rodents affords researchers a powerful translational tool to directly assess/explore the effects of various pharmacological, lesion, and/or disease states on known neural circuits within highly controlled settings. Integration of animal and human research at the molecular-, systems-, and behavioral-levels using diverse neuroimaging techniques empowers more robust interrogations of abnormal/ pathological processes, critical for evolving our understanding of neuroscience. We present a comprehensive protocol to evaluate resting-state brain networks using Independent Component Analysis (ICA) in rodent model. Specifically, we begin with a brief review of the physiological basis for rs-fMRI technique and overview of rs-fMRI studies in rodents to date, following which we provide a robust step-by-step approach for rs-fMRI investigation including data collection, computational preprocessing, and brain network analysis. Pipelines are interwoven with underlying theory behind each step and summarized methodological considerations, such as alternative methods available and current consensus in the literature for optimal results. The presented protocol is designed in such a way that investigators without previous knowledge in the field can implement the analysis and obtain viable results that reliably detect significant differences in functional connectivity between experimental groups. Our goal is to empower researchers to implement rs-fMRI in their respective fields by incorporating technical considerations to date into a workable methodological framework. PMID:29311770

Toward reliable characterization of functional homogeneity in the human brain: Preprocessing, scan duration, imaging resolution and computational space

PubMed Central

Zuo, Xi-Nian; Xu, Ting; Jiang, Lili; Yang, Zhi; Cao, Xiao-Yan; He, Yong; Zang, Yu-Feng; Castellanos, F. Xavier; Milham, Michael P.

2013-01-01

While researchers have extensively characterized functional connectivity between brain regions, the characterization of functional homogeneity within a region of the brain connectome is in early stages of development. Several functional homogeneity measures were proposed previously, among which regional homogeneity (ReHo) was most widely used as a measure to characterize functional homogeneity of resting state fMRI (R-fMRI) signals within a small region (Zang et al., 2004). Despite a burgeoning literature on ReHo in the field of neuroimaging brain disorders, its test–retest (TRT) reliability remains unestablished. Using two sets of public R-fMRI TRT data, we systematically evaluated the ReHo’s TRT reliability and further investigated the various factors influencing its reliability and found: 1) nuisance (head motion, white matter, and cerebrospinal fluid) correction of R-fMRI time series can significantly improve the TRT reliability of ReHo while additional removal of global brain signal reduces its reliability, 2) spatial smoothing of R-fMRI time series artificially enhances ReHo intensity and influences its reliability, 3) surface-based R-fMRI computation largely improves the TRT reliability of ReHo, 4) a scan duration of 5 min can achieve reliable estimates of ReHo, and 5) fast sampling rates of R-fMRI dramatically increase the reliability of ReHo. Inspired by these findings and seeking a highly reliable approach to exploratory analysis of the human functional connectome, we established an R-fMRI pipeline to conduct ReHo computations in both 3-dimensions (volume) and 2-dimensions (surface). PMID:23085497

Functional Magnetic Resonance Imaging (fMRI) Neurofeedback: Implementations and Applications

PubMed Central

DEWIPUTRI, Wan Ilma; AUER, Tibor

2013-01-01

Neurofeedback (NFB) allows subjects to learn how to volitionally influence the neuronal activation in the brain by employing real-time neural activity as feedback. NFB has already been performed with electroencephalography (EEG) since the 1970s. Functional MRI (fMRI), offering a higher spatial resolution, has further increased the spatial specificity. In this paper, we briefly outline the general principles behind NFB, the implementation of fMRI-NFB studies, the feasibility of fMRI-NFB, and the application of NFB as a supplementary therapy tool. PMID:24643368

219. Changes in Functional Networks Underlying Social Cognition Following Cognitive Training in Individuals at Risk for Psychosis

PubMed Central

Haut, Kristen; Saxena, Abhishek; Yin, Hong; Carol, Emily; Dodell-Feder, David; Lincoln, Sarah Hope; Tully, Laura; Keshavan, Matcheri; Seidman, Larry J.; Nahum, Mor; Hooker, Christine

2017-01-01

Abstract Background: Deficits in social cognition are prominent features of schizophrenia that play a large role in functional impairments and disability. Performance deficits in these domains are associated with altered activity in functional networks, including those that support social cognitive abilities such as emotion recognition. These social cognitive deficits and alterations in neural networks are present prior to the onset of frank psychotic symptoms and thus present a potential target for intervention in early phases of the illness, including in individuals at clinical high risk (CHR) for psychosis. This study assessed changes in social cognitive functional networks following targeted cognitive training (TCT) in CHR individuals. Methods: 14 CHR subjects (7 male, mean age = 21.9) showing attenuated psychotic symptoms as assessed by the SIPS were included in the study. Subjects underwent a clinical evaluation and a functional MRI session prior to and subsequent to completing 40 hours (8 weeks) of targeted cognitive and social cognitive training using Lumosity and SocialVille. 14 matched healthy control (HC) subjects also underwent a single fMRI session as a comparison group for functional activity. Resting state fMRI was acquired as well as fMRI during performance of an emotion recognition task. Group level differences in BOLD activity between HC and CHR group before TCT, and CHR group before and after TCT were computed. Changes in social cognitive network functional connectivity at rest and during task performance was evaluated using seed-based connectivity analyses and psychophysiological interaction (PPI). Results: Prior to training, CHR individuals demonstrated hyperactivity in the amygdala, posterior cingulate, and superior temporal sulcus (STS) during emotion recognition, suggesting inefficient processing. This hyperactivity normalized somewhat after training, with CHR individuals showing less hyperactivity in the amygdala in response to emotional faces. In addition, training was associated with increased connectivity in emotion processing networks, including greater STS-medial prefrontal connectivity and normalization of amygdala connectivity patterns. Conclusion: These results suggest that targeted cognitive training produced improvements in emotion recognition and may be effective in altering functional network connectivity in networks associated with psychosis risk. TCT may be a useful tool for early intervention in individuals at risk for psychotic disorders to address behaviors that impact functional outcome.

Implementation of compressive sensing for preclinical cine-MRI

NASA Astrophysics Data System (ADS)

Tan, Elliot; Yang, Ming; Ma, Lixin; Zheng, Yahong Rosa

2014-03-01

This paper presents a practical implementation of Compressive Sensing (CS) for a preclinical MRI machine to acquire randomly undersampled k-space data in cardiac function imaging applications. First, random undersampling masks were generated based on Gaussian, Cauchy, wrapped Cauchy and von Mises probability distribution functions by the inverse transform method. The best masks for undersampling ratios of 0.3, 0.4 and 0.5 were chosen for animal experimentation, and were programmed into a Bruker Avance III BioSpec 7.0T MRI system through method programming in ParaVision. Three undersampled mouse heart datasets were obtained using a fast low angle shot (FLASH) sequence, along with a control undersampled phantom dataset. ECG and respiratory gating was used to obtain high quality images. After CS reconstructions were applied to all acquired data, resulting images were quantitatively analyzed using the performance metrics of reconstruction error and Structural Similarity Index (SSIM). The comparative analysis indicated that CS reconstructed images from MRI machine undersampled data were indeed comparable to CS reconstructed images from retrospective undersampled data, and that CS techniques are practical in a preclinical setting. The implementation achieved 2 to 4 times acceleration for image acquisition and satisfactory quality of image reconstruction.

Preoperative three-dimensional model creation of magnetic resonance brain images as a tool to assist neurosurgical planning.

PubMed

Spottiswoode, B S; van den Heever, D J; Chang, Y; Engelhardt, S; Du Plessis, S; Nicolls, F; Hartzenberg, H B; Gretschel, A

2013-01-01

Neurosurgeons regularly plan their surgery using magnetic resonance imaging (MRI) images, which may show a clear distinction between the area to be resected and the surrounding healthy brain tissue depending on the nature of the pathology. However, this distinction is often unclear with the naked eye during the surgical intervention, and it may be difficult to infer depth and an accurate volumetric interpretation from a series of MRI image slices. In this work, MRI data are used to create affordable patient-specific 3-dimensional (3D) scale models of the brain which clearly indicate the location and extent of a tumour relative to brain surface features and important adjacent structures. This is achieved using custom software and rapid prototyping. In addition, functionally eloquent areas identified using functional MRI are integrated into the 3D models. Preliminary in vivo results are presented for 2 patients. The accuracy of the technique was estimated both theoretically and by printing a geometrical phantom, with mean dimensional errors of less than 0.5 mm observed. This may provide a practical and cost-effective tool which can be used for training, and during neurosurgical planning and intervention. Copyright © 2013 S. Karger AG, Basel.

Diffusion tensor tracking of neuronal fiber pathways in the living human brain

NASA Astrophysics Data System (ADS)

Lori, Nicolas Francisco

2001-11-01

The technique of diffusion tensor tracking (DTT) is described, in which diffusion tensor magnetic resonance imaging (DT-MRI) data are processed to allow the visualization of white matter (WM) tracts in a living human brain. To illustrate the methods, a detailed description is given of the physics of DT-MRI, the structure of the DT-MRI experiment, the computer tools that were developed to visualize WM tracts, the anatomical consistency of the obtained WM tracts, and the accuracy and precision of DTT using computer simulations. When presenting the physics of DT-MRI, a completely quantum-mechanical view of DT-MRI is given where some of the results are new. Examples of anatomical tracts viewed using DTT are presented, including the genu and the splenium of the corpus callosum, the ventral pathway with its amygdala connection highlighted, the geniculo- calcarine tract separated into anterior and posterior parts, the geniculo-calcarine tract defined using functional magnetic resonance imaging (MRI), and U- fibers. In the simulation, synthetic DT-MRI data were constructed that would be obtained for a cylindrical WM tract with a helical trajectory surrounded by gray matter. Noise was then added to the synthetic DT-MRI data, and DTT trajectories were calculated using the noisy data (realistic tracks). Simulated DTT errors were calculated as the vector distance between the realistic tracks and the ideal trajectory. The simulation tested the effects of a comprehensive set of experimental conditions, including voxel size, data sampling, data averaging, type of tract tissue, tract diameter and type of tract trajectory. Simulated DTT accuracy and precision were typically below the voxel dimension, and precision was compatible with the experimental results.

Classification of fMRI independent components using IC-fingerprints and support vector machine classifiers.

PubMed

De Martino, Federico; Gentile, Francesco; Esposito, Fabrizio; Balsi, Marco; Di Salle, Francesco; Goebel, Rainer; Formisano, Elia

2007-01-01

We present a general method for the classification of independent components (ICs) extracted from functional MRI (fMRI) data sets. The method consists of two steps. In the first step, each fMRI-IC is associated with an IC-fingerprint, i.e., a representation of the component in a multidimensional space of parameters. These parameters are post hoc estimates of global properties of the ICs and are largely independent of a specific experimental design and stimulus timing. In the second step a machine learning algorithm automatically separates the IC-fingerprints into six general classes after preliminary training performed on a small subset of expert-labeled components. We illustrate this approach in a multisubject fMRI study employing visual structure-from-motion stimuli encoding faces and control random shapes. We show that: (1) IC-fingerprints are a valuable tool for the inspection, characterization and selection of fMRI-ICs and (2) automatic classifications of fMRI-ICs in new subjects present a high correspondence with those obtained by expert visual inspection of the components. Importantly, our classification procedure highlights several neurophysiologically interesting processes. The most intriguing of which is reflected, with high intra- and inter-subject reproducibility, in one IC exhibiting a transiently task-related activation in the 'face' region of the primary sensorimotor cortex. This suggests that in addition to or as part of the mirror system, somatotopic regions of the sensorimotor cortex are involved in disambiguating the perception of a moving body part. Finally, we show that the same classification algorithm can be successfully applied, without re-training, to fMRI collected using acquisition parameters, stimulation modality and timing considerably different from those used for training.

Instrumentation and method for measuring NIR light absorbed in tissue during MR imaging in medical NIRS measurements

NASA Astrophysics Data System (ADS)

Myllylä, Teemu S.; Sorvoja, Hannu S. S.; Nikkinen, Juha; Tervonen, Osmo; Kiviniemi, Vesa; Myllylä, Risto A.

2011-07-01

Our goal is to provide a cost-effective method for examining human tissue, particularly the brain, by the simultaneous use of functional magnetic resonance imaging (fMRI) and near-infrared spectroscopy (NIRS). Due to its compatibility requirements, MRI poses a demanding challenge for NIRS measurements. This paper focuses particularly on presenting the instrumentation and a method for the non-invasive measurement of NIR light absorbed in human tissue during MR imaging. One practical method to avoid disturbances in MR imaging involves using long fibre bundles to enable conducting the measurements at some distance from the MRI scanner. This setup serves in fact a dual purpose, since also the NIRS device will be less disturbed by the MRI scanner. However, measurements based on long fibre bundles suffer from light attenuation. Furthermore, because one of our primary goals was to make the measuring method as cost-effective as possible, we used high-power light emitting diodes instead of more expensive lasers. The use of LEDs, however, limits the maximum output power which can be extracted to illuminate the tissue. To meet these requirements, we improved methods of emitting light sufficiently deep into tissue. We also show how to measure NIR light of a very small power level that scatters from the tissue in the MRI environment, which is characterized by strong electromagnetic interference. In this paper, we present the implemented instrumentation and measuring method and report on test measurements conducted during MRI scanning. These measurements were performed in MRI operating rooms housing 1.5 Tesla-strength closed MRI scanners (manufactured by GE) in the Dept. of Diagnostic Radiology at the Oulu University Hospital.

Magnetic resonance imaging of female prostate pathology.

PubMed

Wimpissinger, Florian; Tscherney, Robert; Stackl, Walter

2009-06-01

The female prostate (paraurethral glands) is a well-known, yet poorly understood, anatomic structure. Imaging studies of the female prostate, its physiology, and pathologies are still highly controversial. To study the anatomy of the female prostate with contemporary magnetic resonance imaging (MRI) techniques and correlate these findings to clinical features. Female prostate pathologic anatomy on MRI. Women with clinical signs of function (or dysfunction) of paraurethral glands have been examined with 1.5 or 3 Tesla MRI and urethroscopy. Seven women aged 17 to 62 years (median 40 years) have been prospectively included into the study. Clinically, one of the seven women reported ejaculation at orgasm, whereas three women presented with occasional secretions independent of sexual stimulation. In two women, paraurethral glands have been randomly found on MRI that has been performed in the diagnostic workup of other diseases. One woman presented with swelling of the external urethral meatus at puberty. In this woman, a paraurethral gland has been found, besides the erectile tissue at the external meatus. Two women reported lower urinary tract symptoms (LUTS) with mainly urethral symptoms (recurrent infections in one and paraurethral stones in the other). On MRI, paraurethral glands could be visualized in six of the seven patients. There was no relation between glandular volume and ejaculation status. In cases where glands or related pathologies could be found on physical examination, there was a clear correlation with MRI anatomy. MRI has the potential to become the standard imaging modality for female prostate pathology. Exact visualization of this highly variable structure is possible by tailored MRI protocols. This tool can aid in understanding an individual woman's symptoms related to paraurethral glands with an impact on her sexual life.

Advanced approach for intraoperative MRI guidance and potential benefit for neurosurgical applications.

PubMed

Busse, Harald; Schmitgen, Arno; Trantakis, Christos; Schober, Ralf; Kahn, Thomas; Moche, Michael

2006-07-01

To present an advanced approach for intraoperative image guidance in an open 0.5 T MRI and to evaluate its effectiveness for neurosurgical interventions by comparison with a dynamic scan-guided localization technique. The built-in scan guidance mode relied on successive interactive MRI scans. The additional advanced mode provided real-time navigation based on reformatted high-quality, intraoperatively acquired MR reference data, allowed multimodal image fusion, and used the successive scans of the built-in mode for quick verification of the position only. Analysis involved tumor resections and biopsies in either scan guidance (N = 36) or advanced mode (N = 59) by the same three neurosurgeons. Technical, surgical, and workflow aspects were compared. The image quality and hand-eye coordination of the advanced approach were improved. While the average extent of resection, neurologic outcome after functional MRI (fMRI) integration, and diagnostic yield appeared to be slightly better under advanced guidance, particularly for the main surgeon, statistical analysis revealed no significant differences. Resection times were comparable, while biopsies took around 30 minutes longer. The presented approach is safe and provides more detailed images and higher navigation speed at the expense of actuality. The surgical outcome achieved with advanced guidance is (at least) as good as that obtained with dynamic scan guidance. (c) 2006 Wiley-Liss, Inc.

Fixation-related FMRI analysis in the domain of reading research: using self-paced eye movements as markers for hemodynamic brain responses during visual letter string processing.

PubMed

Richlan, Fabio; Gagl, Benjamin; Hawelka, Stefan; Braun, Mario; Schurz, Matthias; Kronbichler, Martin; Hutzler, Florian

2014-10-01

The present study investigated the feasibility of using self-paced eye movements during reading (measured by an eye tracker) as markers for calculating hemodynamic brain responses measured by functional magnetic resonance imaging (fMRI). Specifically, we were interested in whether the fixation-related fMRI analysis approach was sensitive enough to detect activation differences between reading material (words and pseudowords) and nonreading material (line and unfamiliar Hebrew strings). Reliable reading-related activation was identified in left hemisphere superior temporal, middle temporal, and occipito-temporal regions including the visual word form area (VWFA). The results of the present study are encouraging insofar as fixation-related analysis could be used in future fMRI studies to clarify some of the inconsistent findings in the literature regarding the VWFA. Our study is the first step in investigating specific visual word recognition processes during self-paced natural sentence reading via simultaneous eye tracking and fMRI, thus aiming at an ecologically valid measurement of reading processes. We provided the proof of concept and methodological framework for the analysis of fixation-related fMRI activation in the domain of reading research. © The Author 2013. Published by Oxford University Press.

The value of magnetic resonance imaging as a biomarker for amyotrophic lateral sclerosis: a systematic review.

PubMed

Grolez, G; Moreau, C; Danel-Brunaud, V; Delmaire, C; Lopes, R; Pradat, P F; El Mendili, M M; Defebvre, L; Devos, D

2016-08-27

Amyotrophic lateral sclerosis (ALS) is a fatal, rapidly progressive neurodegenerative disease that mainly affects the motor system. A number of potentially neuroprotective and neurorestorative disease-modifying drugs are currently in clinical development. At present, the evaluation of a drug's clinical efficacy in ALS is based on the ALS Functional Rating Scale Revised, motor tests and survival. However, these endpoints are general, variable and late-stage measures of the ALS disease process and thus require the long-term assessment of large cohorts. Hence, there is a need for more sensitive radiological biomarkers. Various sequences for magnetic resonance imaging (MRI) of the brain and spinal cord have may have value as surrogate biomarkers for use in future clinical trials. Here, we review the MRI findings in ALS, their clinical correlations, and their limitations and potential role as biomarkers. The PubMed database was screened to identify studies using MRI in ALS. We included general MRI studies with a control group and an ALS group and longitudinal studies even if a control group was lacking. A total of 116 studies were analysed with MRI data and clinical correlations. The most disease-sensitive MRI patterns are in motor regions but the brain is more broadly affected. Despite the existing MRI biomarkers, there is a need for large cohorts with long term MRI and clinical follow-up. MRI assessment could be improved by standardized MRI protocols with multicentre studies.

Effect of Acupuncture on Functional Connectivity of Anterior Cingulate Cortex for Bell's Palsy Patients with Different Clinical Duration

PubMed Central

Wu, Hongli; Kan, Hongxing; Li, Chuanfu; Park, Kyungmo; Zhu, Yifang; Mohamed, Abdalla Z.; Xu, Chunsheng; Wu, Yuanyuan; Zhang, Wei

2015-01-01

Acupuncture is widely used in the treatment of Bell's palsy (BP) in many countries, but its underlying physiological mechanism remained controversial. In order to explore the potential mechanism, changes of functional connectivity (FC) of anterior cingulate gyrus (ACC) were investigated. We collected 20 healthy (control group) participants and 28 BP patients with different clinical duration accepted resting state functional MRI (rfMRI) scans before and after acupuncture, respectively. The FC of ACC before and after acupuncture was compared with paired t-test and the detailed results are presented in the paper. Our results showed that effects of the acupuncture on FC were closely related to clinical duration in patients with BP, which suggested that brain response to acupuncture was closely connected with the status of brain functional connectivity and implied that acupuncture plays a homeostatic role in the BP treatment. PMID:26161125

Impaired glymphatic perfusion after strokes revealed by contrast-enhanced MRI: a new target for fibrinolysis?

PubMed

Gaberel, Thomas; Gakuba, Clement; Goulay, Romain; Martinez De Lizarrondo, Sara; Hanouz, Jean-Luc; Emery, Evelyne; Touze, Emmanuel; Vivien, Denis; Gauberti, Maxime

2014-10-01

The aim of the present study was to investigate the impact of different stroke subtypes on the glymphatic system using MRI. We first improved and characterized an in vivo protocol to measure the perfusion of the glymphatic system using MRI after minimally invasive injection of a gadolinium chelate within the cisterna magna. Then, the integrity of the glymphatic system was evaluated in 4 stroke models in mice including subarachnoid hemorrhage (SAH), intracerebral hemorrhage, carotid ligature, and embolic ischemic stroke. We were able to reliably evaluate the glymphatic system function using MRI. Moreover, we provided evidence that the glymphatic system was severely impaired after SAH and in the acute phase of ischemic stroke, but was not altered after carotid ligature or in case of intracerebral hemorrhage. Notably, this alteration in glymphatic perfusion reduced brain clearance rate of low-molecular-weight compounds. Interestingly, glymphatic perfusion after SAH can be improved by intracerebroventricular injection of tissue-type plasminogen activator. Moreover, spontaneous arterial recanalization was associated with restoration of the glymphatic function after embolic ischemic stroke. SAH and acute ischemic stroke significantly impair the glymphatic system perfusion. In these contexts, injection of tissue-type plasminogen activator either intracerebroventricularly to clear perivascular spaces (for SAH) or intravenously to restore arterial patency (for ischemic stroke) may improve glymphatic function. © 2014 American Heart Association, Inc.

Decoding Lifespan Changes of the Human Brain Using Resting-State Functional Connectivity MRI

PubMed Central

Wang, Lubin; Su, Longfei; Shen, Hui; Hu, Dewen

2012-01-01

The development of large-scale functional brain networks is a complex, lifelong process that can be investigated using resting-state functional connectivity MRI (rs-fcMRI). In this study, we aimed to decode the developmental dynamics of the whole-brain functional network in seven decades (8–79 years) of the human lifespan. We first used parametric curve fitting to examine linear and nonlinear age effect on the resting human brain, and then combined manifold learning and support vector machine methods to predict individuals' “brain ages” from rs-fcMRI data. We found that age-related changes in interregional functional connectivity exhibited spatially and temporally specific patterns. During brain development from childhood to senescence, functional connections tended to linearly increase in the emotion system and decrease in the sensorimotor system; while quadratic trajectories were observed in functional connections related to higher-order cognitive functions. The complex patterns of age effect on the whole-brain functional network could be effectively represented by a low-dimensional, nonlinear manifold embedded in the functional connectivity space, which uncovered the inherent structure of brain maturation and aging. Regression of manifold coordinates with age further showed that the manifold representation extracted sufficient information from rs-fcMRI data to make prediction about individual brains' functional development levels. Our study not only gives insights into the neural substrates that underlie behavioral and cognitive changes over age, but also provides a possible way to quantitatively describe the typical and atypical developmental progression of human brain function using rs-fcMRI. PMID:22952990

Decoding lifespan changes of the human brain using resting-state functional connectivity MRI.

PubMed

Wang, Lubin; Su, Longfei; Shen, Hui; Hu, Dewen

2012-01-01

The development of large-scale functional brain networks is a complex, lifelong process that can be investigated using resting-state functional connectivity MRI (rs-fcMRI). In this study, we aimed to decode the developmental dynamics of the whole-brain functional network in seven decades (8-79 years) of the human lifespan. We first used parametric curve fitting to examine linear and nonlinear age effect on the resting human brain, and then combined manifold learning and support vector machine methods to predict individuals' "brain ages" from rs-fcMRI data. We found that age-related changes in interregional functional connectivity exhibited spatially and temporally specific patterns. During brain development from childhood to senescence, functional connections tended to linearly increase in the emotion system and decrease in the sensorimotor system; while quadratic trajectories were observed in functional connections related to higher-order cognitive functions. The complex patterns of age effect on the whole-brain functional network could be effectively represented by a low-dimensional, nonlinear manifold embedded in the functional connectivity space, which uncovered the inherent structure of brain maturation and aging. Regression of manifold coordinates with age further showed that the manifold representation extracted sufficient information from rs-fcMRI data to make prediction about individual brains' functional development levels. Our study not only gives insights into the neural substrates that underlie behavioral and cognitive changes over age, but also provides a possible way to quantitatively describe the typical and atypical developmental progression of human brain function using rs-fcMRI.

Alterations of functional connectivities from early to middle adulthood: Clues from multivariate pattern analysis of resting-state fMRI data.

PubMed

Tian, Lixia; Ma, Lin; Wang, Linlin

2016-04-01

In contrast to extended research interests in the maturation and aging of human brain, alterations of brain structure and function from early to middle adulthood have been much less studied. The aim of the present study was to investigate the extent and pattern of the alterations of functional interactions between brain regions from early to middle adulthood. We carried out the study by multivariate pattern analysis of resting-state fMRI (RS-fMRI) data of 63 adults aged 18 to 45 years. Specifically, using elastic net, we performed brain age estimation and age-group classification (young adults aged 18-28 years vs. middle-aged adults aged 35-45 years) based on the resting-state functional connectivities (RSFCs) between 160 regions of interest (ROIs) evaluated on the RS-fMRI data of each subject. The results indicate that the estimated brain ages were significantly correlated with the chronological age (R=0.78, MAE=4.81), and a classification rate of 94.44% and area under the receiver operating characteristic curve (AUC) of 0.99 were obtained when classifying the young and middle-aged adults. These results provide strong evidence that functional interactions between brain regions undergo notable alterations from early to middle adulthood. By analyzing the RSFCs that contribute to brain age estimation/age-group classification, we found that a majority of the RSFCs were inter-network, and we speculate that inter-network RSFCs might mature late but age early as compared to intra-network ones. In addition, the strengthening/weakening of the RSFCs associated with the left/right hemispheric ROIs, the weakening of cortico-cerebellar RSFCs and the strengthening of the RSFCs between the default mode network and other networks contributed much to both brain age estimation and age-group classification. All these alterations might reflect that aging of brain function is already in progress in middle adulthood. Overall, the present study indicated that the RSFCs undergo notable alterations from early to middle adulthood and highlighted the necessity of careful considerations of possible influences of these alterations in related studies. Copyright © 2016 Elsevier Inc. All rights reserved.

Thalamo-Sensorimotor Functional Connectivity Correlates with World Ranking of Olympic, Elite, and High Performance Athletes.

PubMed

Huang, Zirui; Davis, Henry Hap; Wolff, Annemarie; Northoff, Georg

2017-01-01

Brain plasticity studies have shown functional reorganization in participants with outstanding motor expertise. Little is known about neural plasticity associated with exceptionally long motor training or of its predictive value for motor performance excellence. The present study utilised resting-state functional magnetic resonance imaging (rs-fMRI) in a unique sample of world-class athletes: Olympic, elite, and internationally ranked swimmers ( n = 30). Their world ranking ranged from 1st to 250th: each had prepared for participation in the Olympic Games. Combining rs-fMRI graph-theoretical and seed-based functional connectivity analyses, it was discovered that the thalamus has its strongest connections with the sensorimotor network in elite swimmers with the highest world rankings (career best rank: 1-35). Strikingly, thalamo-sensorimotor functional connections were highly correlated with the swimmers' motor performance excellence, that is, accounting for 41% of the individual variance in best world ranking. Our findings shed light on neural correlates of long-term athletic performance involving thalamo-sensorimotor functional circuits.

Ridding fMRI data of motion-related influences: Removal of signals with distinct spatial and physical bases in multiecho data.

PubMed

Power, Jonathan D; Plitt, Mark; Gotts, Stephen J; Kundu, Prantik; Voon, Valerie; Bandettini, Peter A; Martin, Alex

2018-02-27

"Functional connectivity" techniques are commonplace tools for studying brain organization. A critical element of these analyses is to distinguish variance due to neurobiological signals from variance due to nonneurobiological signals. Multiecho fMRI techniques are a promising means for making such distinctions based on signal decay properties. Here, we report that multiecho fMRI techniques enable excellent removal of certain kinds of artifactual variance, namely, spatially focal artifacts due to motion. By removing these artifacts, multiecho techniques reveal frequent, large-amplitude blood oxygen level-dependent (BOLD) signal changes present across all gray matter that are also linked to motion. These whole-brain BOLD signals could reflect widespread neural processes or other processes, such as alterations in blood partial pressure of carbon dioxide (pCO 2 ) due to ventilation changes. By acquiring multiecho data while monitoring breathing, we demonstrate that whole-brain BOLD signals in the resting state are often caused by changes in breathing that co-occur with head motion. These widespread respiratory fMRI signals cannot be isolated from neurobiological signals by multiecho techniques because they occur via the same BOLD mechanism. Respiratory signals must therefore be removed by some other technique to isolate neurobiological covariance in fMRI time series. Several methods for removing global artifacts are demonstrated and compared, and were found to yield fMRI time series essentially free of motion-related influences. These results identify two kinds of motion-associated fMRI variance, with different physical mechanisms and spatial profiles, each of which strongly and differentially influences functional connectivity patterns. Distance-dependent patterns in covariance are nearly entirely attributable to non-BOLD artifacts.

The Neurological Basis and Potential Modification of Emotional Intelligence through Affective/Behavioral Training

DTIC Science & Technology

2010-10-01

facial trustworthiness; facial displays of anger) presented subliminally . Furthermore, the responsiveness of these regions to subliminal stimulation ...develop, or program the computerized stimulation paradigms for use during functional neuroimaging (i.e., MJT; BMAT; EFAT). These paradigms will be...programming began on the computerized functional MRI stimulation paradigms using e-prime software. • Quarter #2: Programming of all computerized functional

RETROSPECTIVE DETECTION OF INTERLEAVED SLICE ACQUISITION PARAMETERS FROM FMRI DATA

PubMed Central

Parker, David; Rotival, Georges; Laine, Andrew; Razlighi, Qolamreza R.

2015-01-01

To minimize slice excitation leakage to adjacent slices, interleaved slice acquisition is nowadays performed regularly in fMRI scanners. In interleaved slice acquisition, the number of slices skipped between two consecutive slice acquisitions is often referred to as the ‘interleave parameter’; the loss of this parameter can be catastrophic for the analysis of fMRI data. In this article we present a method to retrospectively detect the interleave parameter and the axis in which it is applied. Our method relies on the smoothness of the temporal-distance correlation function, which becomes disrupted along the axis on which interleaved slice acquisition is applied. We examined this method on simulated and real data in the presence of fMRI artifacts such as physiological noise, motion, etc. We also examined the reliability of this method in detecting different types of interleave parameters and demonstrated an accuracy of about 94% in more than 1000 real fMRI scans. PMID:26161244

2D dose distribution images of a hybrid low field MRI-γ detector

NASA Astrophysics Data System (ADS)

Abril, A.; Agulles-Pedrós, L.

2016-07-01

The proposed hybrid system is a combination of a low field MRI and dosimetric gel as a γ detector. The readout system is based on the polymerization process induced by the gel radiation. A gel dose map is obtained which represents the functional part of hybrid image alongside with the anatomical MRI one. Both images should be taken while the patient with a radiopharmaceutical is located inside the MRI system with a gel detector matrix. A relevant aspect of this proposal is that the dosimetric gel has never been used to acquire medical images. The results presented show the interaction of the 99mTc source with the dosimetric gel simulated in Geant4. The purpose was to obtain the planar γ 2D-image. The different source configurations are studied to explore the ability of the gel as radiation detector through the following parameters; resolution, shape definition and radio-pharmaceutical concentration.

Validation of diffuse optical tomography using a bi-functional optical-MRI contrast agent and a hybrid MRI-DOT system

NASA Astrophysics Data System (ADS)

Luk, Alex T.; Lin, Yuting; Grimmond, Brian; Sood, Anup; Uzgiris, Egidijus E.; Nalcioglu, Orhan; Gulsen, Gultekin

2013-03-01

Since diffuse optical tomography (DOT) is a low spatial resolution modality, it is desirable to validate its quantitative accuracy with another well-established imaging modality, such as magnetic resonance imaging (MRI). In this work, we have used a polymer based bi-functional MRI-optical contrast agent (Gd-DTPA-polylysine-IR800) in collaboration with GE Global Research. This multi-modality contrast agent provided not only co-localization but also the same kinetics, to cross-validate two imaging modalities. Bi-functional agents are injected to the rats and pharmacokinetics at the bladder are recovered using both optical and MR imaging. DOT results are validated using MRI results as "gold standard"

High-field fMRI unveils orientation columns in humans.

PubMed

Yacoub, Essa; Harel, Noam; Ugurbil, Kâmil

2008-07-29

Functional (f)MRI has revolutionized the field of human brain research. fMRI can noninvasively map the spatial architecture of brain function via localized increases in blood flow after sensory or cognitive stimulation. Recent advances in fMRI have led to enhanced sensitivity and spatial accuracy of the measured signals, indicating the possibility of detecting small neuronal ensembles that constitute fundamental computational units in the brain, such as cortical columns. Orientation columns in visual cortex are perhaps the best known example of such a functional organization in the brain. They cannot be discerned via anatomical characteristics, as with ocular dominance columns. Instead, the elucidation of their organization requires functional imaging methods. However, because of insufficient sensitivity, spatial accuracy, and image resolution of the available mapping techniques, thus far, they have not been detected in humans. Here, we demonstrate, by using high-field (7-T) fMRI, the existence and spatial features of orientation- selective columns in humans. Striking similarities were found with the known spatial features of these columns in monkeys. In addition, we found that a larger number of orientation columns are devoted to processing orientations around 90 degrees (vertical stimuli with horizontal motion), whereas relatively similar fMRI signal changes were observed across any given active column. With the current proliferation of high-field MRI systems and constant evolution of fMRI techniques, this study heralds the exciting prospect of exploring unmapped and/or unknown columnar level functional organizations in the human brain.

INVESTIGATING DIFFERENCES IN BRAIN FUNCTIONAL NETWORKS USING HIERARCHICAL COVARIATE-ADJUSTED INDEPENDENT COMPONENT ANALYSIS.

PubMed

Shi, Ran; Guo, Ying

2016-12-01

Human brains perform tasks via complex functional networks consisting of separated brain regions. A popular approach to characterize brain functional networks in fMRI studies is independent component analysis (ICA), which is a powerful method to reconstruct latent source signals from their linear mixtures. In many fMRI studies, an important goal is to investigate how brain functional networks change according to specific clinical and demographic variabilities. Existing ICA methods, however, cannot directly incorporate covariate effects in ICA decomposition. Heuristic post-ICA analysis to address this need can be inaccurate and inefficient. In this paper, we propose a hierarchical covariate-adjusted ICA (hc-ICA) model that provides a formal statistical framework for estimating covariate effects and testing differences between brain functional networks. Our method provides a more reliable and powerful statistical tool for evaluating group differences in brain functional networks while appropriately controlling for potential confounding factors. We present an analytically tractable EM algorithm to obtain maximum likelihood estimates of our model. We also develop a subspace-based approximate EM that runs significantly faster while retaining high accuracy. To test the differences in functional networks, we introduce a voxel-wise approximate inference procedure which eliminates the need of computationally expensive covariance matrix estimation and inversion. We demonstrate the advantages of our methods over the existing method via simulation studies. We apply our method to an fMRI study to investigate differences in brain functional networks associated with post-traumatic stress disorder (PTSD).

Early indicators of cervical insufficiency assessed using magnetic resonance imaging of the cervix during pregnancy.

PubMed

Habib, Viviane Vieira Francisco; Araujo Júnior, Edward; Sun, Sue Yasaki; Júnior, Dirceu Faggion; Mattar, Rosiane; Szejnfeld, Jacob; Ajzen, Sergio Aron

2015-04-01

To establish the main characteristics of the cervix in pregnant women with cervical insufficiency, by means of magnetic resonance imaging (MRI). A prospective observational case-control study was conducted among 59 pregnant women with cervical insufficiency and 10 normal pregnant women, between their 10th and 28th weeks. The parameters analyzed in the MRI examinations were: precise identification of the cervix; presence of hyposignal at the internal orifice of the cervix; loss of definition of the periendocervical stromal zone (PESZ); presence of hyposignal content inside the amniotic sac (sludge sign) and anatomical and functional biometry of the cervix. Peripheral hyposignal was found in 41 (85.4%) and loss of definition of the PESZ was observed in 36 pregnant women (73.5%) with cervical insufficiency. Sludge was observed in 46 pregnant women with cervical insufficiency, and this was seen on MRI in 27 cases (58.7%). The mean anatomical and functional lengths of the cervix on MRI in the pregnant women with cervical insufficiency were 3.5 ± 0.8 cm (0.8-4.9 cm) and 28.7 ± 6.3 mm (9-41 mm). None of the normal pregnant women presented hyposignal loss of the PESZ and the sludge sign. MRI may be useful for evaluating the cervix and for early identification of signs of cervical insufficiency during pregnancy.

Test-retest and between-site reliability in a multicenter fMRI study.

PubMed

Friedman, Lee; Stern, Hal; Brown, Gregory G; Mathalon, Daniel H; Turner, Jessica; Glover, Gary H; Gollub, Randy L; Lauriello, John; Lim, Kelvin O; Cannon, Tyrone; Greve, Douglas N; Bockholt, Henry Jeremy; Belger, Aysenil; Mueller, Bryon; Doty, Michael J; He, Jianchun; Wells, William; Smyth, Padhraic; Pieper, Steve; Kim, Seyoung; Kubicki, Marek; Vangel, Mark; Potkin, Steven G

2008-08-01

In the present report, estimates of test-retest and between-site reliability of fMRI assessments were produced in the context of a multicenter fMRI reliability study (FBIRN Phase 1, www.nbirn.net). Five subjects were scanned on 10 MRI scanners on two occasions. The fMRI task was a simple block design sensorimotor task. The impulse response functions to the stimulation block were derived using an FIR-deconvolution analysis with FMRISTAT. Six functionally-derived ROIs covering the visual, auditory and motor cortices, created from a prior analysis, were used. Two dependent variables were compared: percent signal change and contrast-to-noise-ratio. Reliability was assessed with intraclass correlation coefficients derived from a variance components analysis. Test-retest reliability was high, but initially, between-site reliability was low, indicating a strong contribution from site and site-by-subject variance. However, a number of factors that can markedly improve between-site reliability were uncovered, including increasing the size of the ROIs, adjusting for smoothness differences, and inclusion of additional runs. By employing multiple steps, between-site reliability for 3T scanners was increased by 123%. Dropping one site at a time and assessing reliability can be a useful method of assessing the sensitivity of the results to particular sites. These findings should provide guidance toothers on the best practices for future multicenter studies.

Noninvasive in vivo tracking of mesenchymal stem cells and evaluation of cell therapeutic effects in a murine model using a clinical 3.0 T MRI.

PubMed

Drey, Florian; Choi, Yeong-Hoon; Neef, Klaus; Ewert, Birgit; Tenbrock, Arne; Treskes, Philipp; Bovenschulte, Henning; Liakopoulos, Oliver J; Brenkmann, Meike; Stamm, Christof; Wittwer, Thorsten; Wahlers, Thorsten

2013-01-01

Cardiac cell therapy with mesenchymal stem cells (MSCs) represents a promising treatment approach for end-stage heart failure. However, little is known about the underlying mechanisms and the fate of the transplanted cells. The objective of the presented work is to determine the feasibility of magnetic resonance imaging (MRI) and in vivo monitoring after transplantation into infarcted mouse hearts using a clinical 3.0 T MRI device. The labeling procedure of bone marrow-derived MSCs with micron-sized paramagnetic iron oxide particles (MPIOs) did not affect the viability of the cells and their cell type-defining properties when compared to unlabeled cells. Using a clinical 3.0 T MRI scanner equipped with a dedicated small animal solenoid coil, 10(5) labeled MSCs could be detected and localized in the mouse hearts for up to 4 weeks after intramyocardial transplantation. Weekly ECG-gated scans using T1-weighted sequences were performed, and left ventricular function was assessed. Histological analysis of hearts confirmed the survival of labeled MSCs in the target area up to 4 weeks after transplantation. In conclusion, in vivo tracking of labeled MSCs using a clinical 3.0 T MRI scanner is feasible. In combination with assessment of heart function, this technology allows the monitoring of the therapeutic efficacy of regenerative therapies in a small animal model.

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.

Structural, functional and spectroscopic MRI studies of methamphetamine addiction.

PubMed

Salo, Ruth; Fassbender, Catherine

2012-01-01

This chapter reviews selected neuroimaging findings related to long-term amphetamine and methamphetamine (MA) use. An overview of structural and functional (fMRI) MR studies, Diffusion Tensor Imaging (DTI), Magnetic Resonance Spectroscopy (MRS) and Positron Emission Tomography (PET) studies conducted in long-term MA abusers is presented. The focus of this chapter is to present the relevant studies as tools to understand brain changes following drug abstinence and recovery from addiction. The behavioral relevance of these neuroimaging studies is discussed as they relate to clinical symptoms and treatment. Within each imaging section this chapter includes a discussion of the relevant imaging studies as they relate to patterns of drug use (i.e., duration of MA use, cumulative lifetime dose and time MA abstinent) as well as an overview of studies that link the imaging findings to cognitive measures. In our conclusion we discuss some of the future directions of neuroimaging as it relates to the pathophysiology of addiction.

Tracking the unconscious generation of free decisions using ultra-high field fMRI.

PubMed

Bode, Stefan; He, Anna Hanxi; Soon, Chun Siong; Trampel, Robert; Turner, Robert; Haynes, John-Dylan

2011-01-01

Recently, we demonstrated using functional magnetic resonance imaging (fMRI) that the outcome of free decisions can be decoded from brain activity several seconds before reaching conscious awareness. Activity patterns in anterior frontopolar cortex (BA 10) were temporally the first to carry intention-related information and thus a candidate region for the unconscious generation of free decisions. In the present study, the original paradigm was replicated and multivariate pattern classification was applied to functional images of frontopolar cortex, acquired using ultra-high field fMRI at 7 Tesla. Here, we show that predictive activity patterns recorded before a decision was made became increasingly stable with increasing temporal proximity to the time point of the conscious decision. Furthermore, detailed questionnaires exploring subjects' thoughts before and during the decision confirmed that decisions were made spontaneously and subjects were unaware of the evolution of their decision outcomes. These results give further evidence that FPC stands at the top of the prefrontal executive hierarchy in the unconscious generation of free decisions.

A 24-ch Phased-Array System for Hyperpolarized Helium Gas Parallel MRI to Evaluate Lung Functions.

PubMed

Lee, Ray; Johnson, Glyn; Stefanescu, Cornel; Trampel, Robert; McGuinness, Georgeann; Stoeckel, Bernd

2005-01-01

Hyperpolarized 3He gas MRI has a serious potential for assessing pulmonary functions. Due to the fact that the non-equilibrium of the gas results in a steady depletion of the signal level over the course of the excitations, the signal-tonoise ratio (SNR) can be independent of the number of the data acquisitions under certain circumstances. This provides a unique opportunity for parallel MRI for gaining both temporal and spatial resolution without reducing SNR. We have built a 24-channel receive / 2-channel transmit phased array system for 3He parallel imaging. Our in vivo experimental results proved that the significant temporal and spatial resolution can be gained at no cost to the SNR. With 3D data acquisition, eight fold (2x4) scan time reduction can be achieved without any aliasing in images. Additionally, a rigid analysis using the low impedance preamplifier for decoupling presented evidence of strong coupling.

A method to classify schizophrenia using inter-task spatial correlations of functional brain images.

PubMed

Michael, Andrew M; Calhoun, Vince D; Andreasen, Nancy C; Baum, Stefi A

2008-01-01

The clinical heterogeneity of schizophrenia (scz) and the overlap of self reported and observed symptoms with other mental disorders makes its diagnosis a difficult task. At present no laboratory-based or image-based diagnostic tool for scz exists and such tools are desired to support existing methods for more precise diagnosis. Functional magnetic resonance imaging (fMRI) is currently employed to identify and correlate cognitive processes related to scz and its symptoms. Fusion of multiple fMRI tasks that probe different cognitive processes may help to better understand hidden networks of this complex disorder. In this paper we utilize three different fMRI tasks and introduce an approach to classify subjects based on inter-task spatial correlations of brain activation. The technique was applied to groups of patients and controls and its validity was checked with the leave-one-out method. We show that the classification rate increases when information from multiple tasks are combined.

Development of the brain's functional network architecture.

PubMed

Vogel, Alecia C; Power, Jonathan D; Petersen, Steven E; Schlaggar, Bradley L

2010-12-01

A full understanding of the development of the brain's functional network architecture requires not only an understanding of developmental changes in neural processing in individual brain regions but also an understanding of changes in inter-regional interactions. Resting state functional connectivity MRI (rs-fcMRI) is increasingly being used to study functional interactions between brain regions in both adults and children. We briefly review methods used to study functional interactions and networks with rs-fcMRI and how these methods have been used to define developmental changes in network functional connectivity. The developmental rs-fcMRI studies to date have found two general properties. First, regional interactions change from being predominately anatomically local in children to interactions spanning longer cortical distances in young adults. Second, this developmental change in functional connectivity occurs, in general, via mechanisms of segregation of local regions and integration of distant regions into disparate subnetworks.

Development of the Brain's Functional Network Architecture

PubMed Central

Power, Jonathan D.; Petersen, Steven E.; Schlaggar, Bradley L.

2013-01-01

A full understanding of the development of the brain's functional network architecture requires not only an understanding of developmental changes in neural processing in individual brain regions but also an understanding of changes in inter-regional interactions. Resting state functional connectivity MRI (rs-fcMRI) is increasingly being used to study functional interactions between brain regions in both adults and children. We briefly review methods used to study functional interactions and networks with rs-fcMRI and how these methods have been used to define developmental changes in network functional connectivity. The developmental rs-fcMRI studies to date have found two general properties. First, regional interactions change from being predominately anatomically local in children to interactions spanning longer cortical distances in young adults. Second, this developmental change in functional connectivity occurs, in general, via mechanisms of segregation of local regions and integration of distant regions into disparate subnetworks. PMID:20976563

Breast MRI: EUSOBI recommendations for women's information.

PubMed

Mann, Ritse M; Balleyguier, Corinne; Baltzer, Pascal A; Bick, Ulrich; Colin, Catherine; Cornford, Eleanor; Evans, Andrew; Fallenberg, Eva; Forrai, Gabor; Fuchsjäger, Michael H; Gilbert, Fiona J; Helbich, Thomas H; Heywang-Köbrunner, Sylvia H; Camps-Herrero, Julia; Kuhl, Christiane K; Martincich, Laura; Pediconi, Federica; Panizza, Pietro; Pina, Luis J; Pijnappel, Ruud M; Pinker-Domenig, Katja; Skaane, Per; Sardanelli, Francesco

2015-12-01

This paper summarizes information about breast MRI to be provided to women and referring physicians. After listing contraindications, procedure details are described, stressing the need for correct scheduling and not moving during the examination. The structured report including BI-RADS® categories and further actions after a breast MRI examination are discussed. Breast MRI is a very sensitive modality, significantly improving screening in high-risk women. It also has a role in clinical diagnosis, problem solving, and staging, impacting on patient management. However, it is not a perfect test, and occasionally breast cancers can be missed. Therefore, clinical and other imaging findings (from mammography/ultrasound) should also be considered. Conversely, MRI may detect lesions not visible on other imaging modalities turning out to be benign (false positives). These risks should be discussed with women before a breast MRI is requested/performed. Because breast MRI drawbacks depend upon the indication for the examination, basic information for the most important breast MRI indications is presented. Seventeen notes and five frequently asked questions formulated for use as direct communication to women are provided. The text was reviewed by Europa Donna-The European Breast Cancer Coalition to ensure that it can be easily understood by women undergoing MRI. • Information on breast MRI concerns advantages/disadvantages and preparation to the examination • Claustrophobia, implantable devices, allergic predisposition, and renal function should be checked • Before menopause, scheduling on day 7-14 of the cycle is preferred • During the examination, it is highly important that the patient keeps still • Availability of prior examinations improves accuracy of breast MRI interpretation.

The contributions of resting state and task-based functional connectivity studies to our understanding of adolescent brain network maturation.

PubMed

Stevens, Michael C

2016-11-01

This review summarizes functional magnetic resonance imaging (fMRI) research done over the past decade that examined changes in the function and organization of brain networks across human adolescence. Its over-arching goal is to highlight how both resting state functional connectivity (rs-fcMRI) and task-based functional connectivity (t-fcMRI) have jointly contributed - albeit in different ways - to our understanding of the scope and types of network organization changes that occur from puberty until young adulthood. These two approaches generally have tested different types of hypotheses using different analysis techniques. This has hampered the convergence of findings. Although much has been learned about system-wide changes to adolescents' neural network organization, if both rs-fcMRI and t-fcMRI approaches draw upon each other's methodology and ask broader questions, it will produce a more detailed connectome-informed theory of adolescent neurodevelopment to guide physiological, clinical, and other lines of research. Copyright © 2016 Elsevier Ltd. All rights reserved.

Implications of neurovascular uncoupling in functional magnetic resonance imaging (fMRI) of brain tumors.

PubMed

Pak, Rebecca W; Hadjiabadi, Darian H; Senarathna, Janaka; Agarwal, Shruti; Thakor, Nitish V; Pillai, Jay J; Pathak, Arvind P

2017-11-01

Functional magnetic resonance imaging (fMRI) serves as a critical tool for presurgical mapping of eloquent cortex and changes in neurological function in patients diagnosed with brain tumors. However, the blood-oxygen-level-dependent (BOLD) contrast mechanism underlying fMRI assumes that neurovascular coupling remains intact during brain tumor progression, and that measured changes in cerebral blood flow (CBF) are correlated with neuronal function. Recent preclinical and clinical studies have demonstrated that even low-grade brain tumors can exhibit neurovascular uncoupling (NVU), which can confound interpretation of fMRI data. Therefore, to avoid neurosurgical complications, it is crucial to understand the biophysical basis of NVU and its impact on fMRI. Here we review the physiology of the neurovascular unit, how it is remodeled, and functionally altered by brain cancer cells. We first discuss the latest findings about the components of the neurovascular unit. Next, we synthesize results from preclinical and clinical studies to illustrate how brain tumor induced NVU affects fMRI data interpretation. We examine advances in functional imaging methods that permit the clinical evaluation of brain tumors with NVU. Finally, we discuss how the suppression of anomalous tumor blood vessel formation with antiangiogenic therapies can "normalize" the brain tumor vasculature, and potentially restore neurovascular coupling.

Coil compression in simultaneous multislice functional MRI with concentric ring slice-GRAPPA and SENSE.

PubMed

Chu, Alan; Noll, Douglas C

2016-10-01

Simultaneous multislice (SMS) imaging is a useful way to accelerate functional magnetic resonance imaging (fMRI). As acceleration becomes more aggressive, an increasingly larger number of receive coils are required to separate the slices, which significantly increases the computational burden. We propose a coil compression method that works with concentric ring non-Cartesian SMS imaging and should work with Cartesian SMS as well. We evaluate the method on fMRI scans of several subjects and compare it to standard coil compression methods. The proposed method uses a slice-separation k-space kernel to simultaneously compress coil data into a set of virtual coils. Five subjects were scanned using both non-SMS fMRI and SMS fMRI with three simultaneous slices. The SMS fMRI scans were processed using the proposed method, along with other conventional methods. Code is available at https://github.com/alcu/sms. The proposed method maintained functional activation with a fewer number of virtual coils than standard SMS coil compression methods. Compression of non-SMS fMRI maintained activation with a slightly lower number of virtual coils than the proposed method, but does not have the acceleration advantages of SMS fMRI. The proposed method is a practical way to compress and reconstruct concentric ring SMS data and improves the preservation of functional activation over standard coil compression methods in fMRI. Magn Reson Med 76:1196-1209, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Functional magnetic resonance imaging (fMRI)-aided therapeutics of Chinese speech area-related lesions: screening of fMRI-stimulating mode and its clinical applications.

PubMed

Wu, Nan; Xie, Bing; Wu, Guo-Cai; Lan, Chuan; Wang, Jian; Feng, Hua

2010-01-01

Language area-related lesion is a serious issue in neurosurgery. Removing the lesion in the language area and at the same time preserving language functions is a great challenge. In this study, we aimed to screen functional magnetic resonance imaging (fMRI) based task types suitable for activation of Broca and Wernicke areas in Chinese population, characterize lesion properties of functional area of Chinese language in brain, and assess the potential of fMRI-guided neuronavigation in clinical applications. Blood oxygen level-dependent fMRI has been used to localize language area prior to operation. We carried out extensive fMRI analyses and conducted operation on patients with lesions in speech area. fMRI tests revealed that the reciting task in Chinese can steadily activate the Broca area, and paragraph comprehension task in Chinese can effectively activate the Wernicke area. Cortical stimulation of patients when being awake during operation validated the sensitivity and accuracy of fMRI. The safe distance between language activation area and removal of the lesion in language area was determined to be about 10 mm. Further investigation suggested that navigation of fMRI combined with diffuse tensor imaging can decrease the incidence of postoperative dysfunction and increase the success rate for complete removal of lesion. Taken together, these findings may be helpful to clinical therapy for language area-related lesions.

Functional Magnetic Resonance Imaging and Functional Near-Infrared Spectroscopy: Insights from Combined Recording Studies

PubMed Central

Scarapicchia, Vanessa; Brown, Cassandra; Mayo, Chantel; Gawryluk, Jodie R.

2017-01-01

Although blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) is a widely available, non-invasive technique that offers excellent spatial resolution, it remains limited by practical constraints imposed by the scanner environment. More recently, functional near infrared spectroscopy (fNIRS) has emerged as an alternative hemodynamic-based approach that possesses a number of strengths where fMRI is limited, most notably in portability and higher tolerance for motion. To date, fNIRS has shown promise in its ability to shed light on the functioning of the human brain in populations and contexts previously inaccessible to fMRI. Notable contributions include infant neuroimaging studies and studies examining full-body behaviors, such as exercise. However, much like fMRI, fNIRS has technical constraints that have limited its application to clinical settings, including a lower spatial resolution and limited depth of recording. Thus, by combining fMRI and fNIRS in such a way that the two methods complement each other, a multimodal imaging approach may allow for more complex research paradigms than is feasible with either technique alone. In light of these issues, the purpose of the current review is to: (1) provide an overview of fMRI and fNIRS and their associated strengths and limitations; (2) review existing combined fMRI-fNIRS recording studies; and (3) discuss how their combined use in future research practices may aid in advancing modern investigations of human brain function. PMID:28867998

Comparison of fMRI data from passive listening and active-response story processing tasks in children

PubMed Central

Vannest, Jennifer J.; Karunanayaka, Prasanna R.; Altaye, Mekibib; Schmithorst, Vincent J.; Plante, Elena M.; Eaton, Kenneth J.; Rasmussen, Jerod M.; Holland, Scott K.

2009-01-01

Purpose To use functional MRI methods to visualize a network of auditory and language-processing brain regions associated with processing an aurally-presented story. We compare a passive listening (PL) story paradigm to an active-response (AR) version including on-line performance monitoring and a sparse acquisition technique. Materials/Methods Twenty children (ages 11−13) completed PL and AR story processing tasks. The PL version presented alternating 30-second blocks of stories and tones; the AR version presented story segments, comprehension questions, and 5s tone sequences, with fMRI acquisitions between stimuli. fMRI data was analyzed using a general linear model approach and paired t-test identifying significant group activation. Results Both tasks activated in primary auditory cortex, superior temporal gyrus bilaterally, left inferior frontal gyrus. The AR task demonstrated more extensive activation, including dorsolateral prefrontal cortex and anterior/posterior cingulate cortex. Comparison of effect size in each paradigm showed a larger effect for the AR paradigm in a left inferior frontal ROI. Conclusion Activation patterns for story processing in children are similar in passive listening and active-response tasks. Increases in extent and magnitude of activation in the AR task are likely associated with memory and attention resources engaged across acquisition intervals. PMID:19306445

Optical/MRI Multimodality Molecular Imaging

NASA Astrophysics Data System (ADS)

Ma, Lixin; Smith, Charles; Yu, Ping

2007-03-01

Multimodality molecular imaging that combines anatomical and functional information has shown promise in development of tumor-targeted pharmaceuticals for cancer detection or therapy. We present a new multimodality imaging technique that combines fluorescence molecular tomography (FMT) and magnetic resonance imaging (MRI) for in vivo molecular imaging of preclinical tumor models. Unlike other optical/MRI systems, the new molecular imaging system uses parallel phase acquisition based on heterodyne principle. The system has a higher accuracy of phase measurements, reduced noise bandwidth, and an efficient modulation of the fluorescence diffuse density waves. Fluorescent Bombesin probes were developed for targeting breast cancer cells and prostate cancer cells. Tissue phantom and small animal experiments were performed for calibration of the imaging system and validation of the targeting probes.

Longitudinal assessment of treatment effects on pulmonary ventilation using 1H/3He MRI multivariate templates

NASA Astrophysics Data System (ADS)

Tustison, Nicholas J.; Contrella, Benjamin; Altes, Talissa A.; Avants, Brian B.; de Lange, Eduard E.; Mugler, John P.

2013-03-01

The utitlity of pulmonary functional imaging techniques, such as hyperpolarized 3He MRI, has encouraged their inclusion in research studies for longitudinal assessment of disease progression and the study of treatment effects. We present methodology for performing voxelwise statistical analysis of ventilation maps derived from hyper­ polarized 3He MRI which incorporates multivariate template construction using simultaneous acquisition of IH and 3He images. Additional processing steps include intensity normalization, bias correction, 4-D longitudinal segmentation, and generation of expected ventilation maps prior to voxelwise regression analysis. Analysis is demonstrated on a cohort of eight individuals with diagnosed cystic fibrosis (CF) undergoing treatment imaged five times every two weeks with a prescribed treatment schedule.

Visual feature extraction from voxel-weighted averaging of stimulus images in 2 fMRI studies.

PubMed

Hart, Corey B; Rose, William J

2013-11-01

Multiple studies have provided evidence for distributed object representation in the brain, with several recent experiments leveraging basis function estimates for partial image reconstruction from fMRI data. Using a novel combination of statistical decomposition, generalized linear models, and stimulus averaging on previously examined image sets and Bayesian regression of recorded fMRI activity during presentation of these data sets, we identify a subset of relevant voxels that appear to code for covarying object features. Using a technique we term "voxel-weighted averaging," we isolate image filters that these voxels appear to implement. The results, though very cursory, appear to have significant implications for hierarchical and deep-learning-type approaches toward the understanding of neural coding and representation.

Bayesian Inference for Functional Dynamics Exploring in fMRI Data.

PubMed

Guo, Xuan; Liu, Bing; Chen, Le; Chen, Guantao; Pan, Yi; Zhang, Jing

2016-01-01

This paper aims to review state-of-the-art Bayesian-inference-based methods applied to functional magnetic resonance imaging (fMRI) data. Particularly, we focus on one specific long-standing challenge in the computational modeling of fMRI datasets: how to effectively explore typical functional interactions from fMRI time series and the corresponding boundaries of temporal segments. Bayesian inference is a method of statistical inference which has been shown to be a powerful tool to encode dependence relationships among the variables with uncertainty. Here we provide an introduction to a group of Bayesian-inference-based methods for fMRI data analysis, which were designed to detect magnitude or functional connectivity change points and to infer their functional interaction patterns based on corresponding temporal boundaries. We also provide a comparison of three popular Bayesian models, that is, Bayesian Magnitude Change Point Model (BMCPM), Bayesian Connectivity Change Point Model (BCCPM), and Dynamic Bayesian Variable Partition Model (DBVPM), and give a summary of their applications. We envision that more delicate Bayesian inference models will be emerging and play increasingly important roles in modeling brain functions in the years to come.

Resting-state fMRI in sleeping infants more closely resembles adult sleep than adult wakefulness

PubMed Central

Snyder, Abraham Z.; Tagliazucchi, Enzo; Laufs, Helmut; Elison, Jed; Emerson, Robert W.; Shen, Mark D.; Wolff, Jason J.; Botteron, Kelly N.; Dager, Stephen; Estes, Annette M.; Evans, Alan; Gerig, Guido; Hazlett, Heather C.; Paterson, Sarah J.; Schultz, Robert T.; Styner, Martin A.; Zwaigenbaum, Lonnie; Schlaggar, Bradley L.

2017-01-01

Resting state functional magnetic resonance imaging (rs-fMRI) in infants enables important studies of functional brain organization early in human development. However, rs-fMRI in infants has universally been obtained during sleep to reduce participant motion artifact, raising the question of whether differences in functional organization between awake adults and sleeping infants that are commonly attributed to development may instead derive, at least in part, from sleep. This question is especially important as rs-fMRI differences in adult wake vs. sleep are well documented. To investigate this question, we compared functional connectivity and BOLD signal propagation patterns in 6, 12, and 24 month old sleeping infants with patterns in adult wakefulness and non-REM sleep. We find that important functional connectivity features seen during infant sleep closely resemble those seen during adult sleep, including reduced default mode network functional connectivity. However, we also find differences between infant and adult sleep, especially in thalamic BOLD signal propagation patterns. These findings highlight the importance of considering sleep state when drawing developmental inferences in infant rs-fMRI. PMID:29149191

Resting-state fMRI in sleeping infants more closely resembles adult sleep than adult wakefulness.

PubMed

Mitra, Anish; Snyder, Abraham Z; Tagliazucchi, Enzo; Laufs, Helmut; Elison, Jed; Emerson, Robert W; Shen, Mark D; Wolff, Jason J; Botteron, Kelly N; Dager, Stephen; Estes, Annette M; Evans, Alan; Gerig, Guido; Hazlett, Heather C; Paterson, Sarah J; Schultz, Robert T; Styner, Martin A; Zwaigenbaum, Lonnie; Schlaggar, Bradley L; Piven, Joseph; Pruett, John R; Raichle, Marcus

2017-01-01

Resting state functional magnetic resonance imaging (rs-fMRI) in infants enables important studies of functional brain organization early in human development. However, rs-fMRI in infants has universally been obtained during sleep to reduce participant motion artifact, raising the question of whether differences in functional organization between awake adults and sleeping infants that are commonly attributed to development may instead derive, at least in part, from sleep. This question is especially important as rs-fMRI differences in adult wake vs. sleep are well documented. To investigate this question, we compared functional connectivity and BOLD signal propagation patterns in 6, 12, and 24 month old sleeping infants with patterns in adult wakefulness and non-REM sleep. We find that important functional connectivity features seen during infant sleep closely resemble those seen during adult sleep, including reduced default mode network functional connectivity. However, we also find differences between infant and adult sleep, especially in thalamic BOLD signal propagation patterns. These findings highlight the importance of considering sleep state when drawing developmental inferences in infant rs-fMRI.

Multimodal MRI in cerebral small vessel disease: its relationship with cognition and sensitivity to change over time.

PubMed

Nitkunan, Arani; Barrick, Tom R; Charlton, Rebecca A; Clark, Chris A; Markus, Hugh S

2008-07-01

Cerebral small vessel disease is the most common cause of vascular dementia. Interest in using MRI parameters as surrogate markers of disease to assess therapies is increasing. In patients with symptomatic sporadic small vessel disease, we determined which MRI parameters best correlated with cognitive function on cross-sectional analysis and which changed over a period of 1 year. Thirty-five patients with lacunar stroke and leukoaraiosis were recruited. They underwent multimodal MRI (brain volume, fluid-attenuated inversion recovery lesion load, lacunar infarct number, fractional anisotropy, and mean diffusivity from diffusion tensor imaging) and neuropsychological testing. Twenty-seven agreed to reattend for repeat MRI and neuropsychology at 1 year. An executive function score correlated most strongly with diffusion tensor imaging (fractional anisotropy histogram, r=-0.640, P=0.004) and brain volume (r=0.501, P=0.034). Associations with diffusion tensor imaging were stronger than with all other MRI parameters. On multiple regression of all imaging parameters, a model that contained brain volume and fractional anisotropy, together with age, gender, and premorbid IQ, explained 74% of the variance of the executive function score (P=0.0001). Changes in mean diffusivity and fractional anisotropy were detectable over the 1-year follow-up; in contrast, no change in other MRI parameters was detectable over this time period. A multimodal MRI model explains a large proportion of the variation in executive function in cerebral small vessel disease. In particular, diffusion tensor imaging correlates best with executive function and is the most sensitive to change. This supports the use of MRI, in particular diffusion tensor imaging, as a surrogate marker in treatment trials.

Functional MRI and intraoperative brain mapping to evaluate brain plasticity in patients with brain tumours and hemiparesis

PubMed Central

Roux, F; Boulanouar, K; Ibarrola, D; Tremoulet, M; Chollet, F; Berry, I

2000-01-01

OBJECTIVE—To support the hypothesis about the potential compensatory role of ipsilateral corticofugal pathways when the contralateral pathways are impaired by brain tumours.
METHODS—Retrospective analysis was carried out on the results of functional MRI (fMRI) of a selected group of five paretic patients with Rolandic brain tumours who exhibited an abnormally high ipsilateral/contralateral ratio of activation—that is, movements of the paretic hand activated predominately the ipsilateral cortex. Brain activation was achieved with a flexion extension of the fingers. Statistical parametric activation was obtained using a t test and a threshold of p<0.001. These patients, candidates for tumour resection, also underwent cortical intraoperative stimulation that was correlated to the fMRI spatial data using three dimensional reconstructions of the brain. Three patients also had postoperative control fMRI.
RESULTS—The absence of fMRI activation of the primary sensorimotor cortex normally innervating the paretic hand for the threshold chosen, was correlated with completely negative cortical responses of the cortical hand area during the operation. The preoperative fMRI activation of these patients predominantly found in the ipsilateral frontal and primary sensorimotor cortices could be related to the residual ipsilateral hand function. Postoperatively, the fMRI activation returned to more classic patterns of activation, reflecting the consequences of therapy.
CONCLUSION—In paretic patients with brain tumours, ipsilateral control could be implicated in the residual hand function, when the normal primary pathways are impaired. The possibility that functional tissue still remains in the peritumorous sensorimotor cortex even when the preoperative fMRI and the cortical intraoperative stimulations are negative, should be taken into account when planning the tumour resection and during the operation.

 PMID:10990503

Early classification of Alzheimer's disease using hippocampal texture from structural MRI

NASA Astrophysics Data System (ADS)

Zhao, Kun; Ding, Yanhui; Wang, Pan; Dou, Xuejiao; Zhou, Bo; Yao, Hongxiang; An, Ningyu; Zhang, Yongxin; Zhang, Xi; Liu, Yong

2017-03-01

Convergent evidence has been collected to support that Alzheimer's disease (AD) is associated with reduction in hippocampal volume based on anatomical magnetic resonance imaging (MRI) and impaired functional connectivity based on functional MRI. Radiomics texture analysis has been previously successfully used to identify MRI biomarkers of several diseases, including AD, mild cognitive impairment and multiple sclerosis. In this study, our goal was to determine if MRI hippocampal textures, including the intensity, shape, texture and wavelet features, could be served as an MRI biomarker of AD. For this purpose, the texture marker was trained and evaluated from MRI data of 48 AD and 39 normal samples. The result highlights the presence of hippocampal texture abnormalities in AD, and the possibility that texture may serve as a neuroimaging biomarker for AD.

TH-CD-202-09: Free-Breathing Proton MRI Functional Lung Avoidance Maps to Guide Radiation Therapy

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

Capaldi, D; Sheikh, K; Parraga, G

Purpose: Pulmonary functional MRI using inhaled gas contrast agents was previously investigated as a way to identify well-functioning lung in patients with NSCLC who are clinical candidates for radiotherapy. Hyperpolarized noble-gas ({sup 3}He and {sup 129}Xe) MRI has also been optimized to measure functional lung information, but for a number of reasons, the clinical translation of this approach to guide radiotherapy planning has been limited. As an alternative, free-breathing pulmonary 1H MRI using clinically available MRI systems and pulse sequences provides a non-contrast-enhanced method to generate both ventilation and perfusion maps. Free-breathing {sup 1}H MRI exploits non-rigid registration and Fouriermore » decomposition of MRI signal intensity differences (Bauman et al., MRM, 2009) that may be generated during normal tidal breathing. Here, our objective was to generate free-breathing {sup 1}H MRI ventilation and lung function avoidance maps in patients with NSCLC as a way to guide radiation therapy planning. Methods: Stage IIIA/IIIB NSCLC patients (n=8, 68±9yr) provided written informed consent to a randomized controlled clinical trial ( https://clinicaltrials.gov/ct2/show/NCT02002052 ) that aimed to compare outcomes related to image-guided versus conventional radiation therapy planning. Hyperpolarized {sup 3}He/{sup 129}Xe and dynamic free tidal-breathing {sup 1}H MRI were acquired as previously described (Capaldi et al., Acad Radiol, 2015). Non-rigid registration was performed using the modality-independent-neighbourhood-descriptor (MIND) deformable approach (Heinrich et al., Med Image Anal, 2012). Ventilation-defect-percent ({sup 3}He:VDP{sub He}, {sup 129}Xe:VDP{sub Xe}, Free-breathing-{sup 1}H:VDP{sub FB}) and the corresponding ventilation maps were compared using Pearson correlation coefficients (r) and the Dice similarity coefficient (DSC). Results: VDP{sub FB} was significantly related to VDP{sub He} (r=.71; p=.04) and VDP{sub Xe} (r=.80; p=.01) and there were also strong spatial relationships (DSC{sub He}/DSC{sub Xe}=89±3%/77±11%). Conclusion: In this proof of concept study in NSCLC patients, free-breathing {sup 1}H MRI ventilation defects were quantitatively and spatially related to inhaled-noble-gas MRI ventilation defects. Free-breathing {sup 1}H MRI measures lung function/ventilation that can be used to optimize radiotherapy planning in NSCLC patients.« less

Reorganization of Functional and Effective Connectivity during Real-Time fMRI-BCI Modulation of Prosody Processing

ERIC Educational Resources Information Center

Rota, Giuseppina; Handjaras, Giacomo; Sitaram, Ranganatha; Birbaumer, Niels; Dogil, Grzegorz

2011-01-01

Mechanisms of cortical reorganization underlying the enhancement of speech processing have been poorly investigated. In the present study, we addressed changes in functional and effective connectivity induced in subjects who learned to deliberately increase activation in the right inferior frontal gyrus (rIFG), and improved their ability to…

Large-scale topology and the default mode network in the mouse connectome

PubMed Central

Stafford, James M.; Jarrett, Benjamin R.; Miranda-Dominguez, Oscar; Mills, Brian D.; Cain, Nicholas; Mihalas, Stefan; Lahvis, Garet P.; Lattal, K. Matthew; Mitchell, Suzanne H.; David, Stephen V.; Fryer, John D.; Nigg, Joel T.; Fair, Damien A.

2014-01-01

Noninvasive functional imaging holds great promise for serving as a translational bridge between human and animal models of various neurological and psychiatric disorders. However, despite a depth of knowledge of the cellular and molecular underpinnings of atypical processes in mouse models, little is known about the large-scale functional architecture measured by functional brain imaging, limiting translation to human conditions. Here, we provide a robust processing pipeline to generate high-resolution, whole-brain resting-state functional connectivity MRI (rs-fcMRI) images in the mouse. Using a mesoscale structural connectome (i.e., an anterograde tracer mapping of axonal projections across the mouse CNS), we show that rs-fcMRI in the mouse has strong structural underpinnings, validating our procedures. We next directly show that large-scale network properties previously identified in primates are present in rodents, although they differ in several ways. Last, we examine the existence of the so-called default mode network (DMN)—a distributed functional brain system identified in primates as being highly important for social cognition and overall brain function and atypically functionally connected across a multitude of disorders. We show the presence of a potential DMN in the mouse brain both structurally and functionally. Together, these studies confirm the presence of basic network properties and functional networks of high translational importance in structural and functional systems in the mouse brain. This work clears the way for an important bridge measurement between human and rodent models, enabling us to make stronger conclusions about how regionally specific cellular and molecular manipulations in mice relate back to humans. PMID:25512496

Localization of Asymmetric Brain Function in Emotion and Depression

PubMed Central

Herrington, John D.; Heller, Wendy; Mohanty, Aprajita; Engels, Anna S.; Banich, Marie T.; Webb, Andrew G.; Miller, Gregory A.

2011-01-01

Although numerous EEG studies have shown that depression is associated with abnormal functional asymmetries in frontal cortex, fMRI and PET studies have largely failed to identify specific brain areas showing this effect. The present study tested the hypothesis that emotion processes are related to asymmetric patterns of fMRI activity, particularly within dorsolateral prefrontal cortex (DLPFC). Eleven depressed and 18 control participants identified the color in which pleasant, neutral, and unpleasant words were printed. Both groups showed a leftward lateralization for pleasant words in DLPFC. In a neighboring DLPFC area, the depression group showed more right-lateralized activation than controls, replicating EEG findings. These data confirm that emotional stimulus processing and trait depression are associated with asymmetric brain functions in distinct subregions of the DLPFC that may go undetected unless appropriate analytic procedures are used. PMID:20070577

Localization of asymmetric brain function in emotion and depression.

PubMed

Herrington, John D; Heller, Wendy; Mohanty, Aprajita; Engels, Anna S; Banich, Marie T; Webb, Andrew G; Miller, Gregory A

2010-05-01

Although numerous EEG studies have shown that depression is associated with abnormal functional asymmetries in frontal cortex, fMRI and PET studies have largely failed to identify specific brain areas showing this effect. The present study tested the hypothesis that emotion processes are related to asymmetric patterns of fMRI activity, particularly within dorsolateral prefrontal cortex (DLPFC). Eleven depressed and 18 control participants identified the color in which pleasant, neutral, and unpleasant words were printed. Both groups showed a leftward lateralization for pleasant words in DLPFC. In a neighboring DLPFC area, the depression group showed more right-lateralized activation than controls, replicating EEG findings. These data confirm that emotional stimulus processing and trait depression are associated with asymmetric brain functions in distinct subregions of the DLPFC that may go undetected unless appropriate analytic procedures are used.

Dissociable corticostriatal circuits underlie goal-directed vs. cue-elicited habitual food seeking after satiation: evidence from a multimodal MRI study.

PubMed

van Steenbergen, Henk; Watson, Poppy; Wiers, Reinout W; Hommel, Bernhard; de Wit, Sanne

2017-07-01

The present multimodal MRI study advances our understanding of the corticostriatal circuits underlying goal-directed vs. cue-driven, habitual food seeking. To this end, we employed a computerized Pavlovian-instrumental transfer paradigm. During the test phase, participants were free to perform learned instrumental responses (left and right key presses) for popcorn and Smarties outcomes. Importantly, prior to this test half of the participants had been sated on popcorn and the other half on Smarties - resulting in a reduced desirability of those outcomes. Furthermore, during a proportion of the test trials, food-associated Pavlovian cues were presented in the background. In line with previous studies, we found that participants were able to perform in a goal-directed manner in the absence of Pavlovian cues, meaning that specific satiation selectively reduced responding for that food. However, presentation of Pavlovian cues biased choice toward the associated food reward regardless of satiation. Functional MRI analyses revealed that, in the absence of Pavlovian cues, posterior ventromedial prefrontal cortex tracked outcome value. In contrast, during cued trials, the BOLD signal in the posterior putamen differentiated between responses compatible and incompatible with the cue-associated outcome. Furthermore, we identified a region in ventral amygdala showing relatively strong functional connectivity with posterior putamen during the cued trials. Structural MRI analyses provided converging evidence for the involvement of corticostriatal circuits: diffusion tensor imaging data revealed that connectivity of caudate-seeded white-matter tracts to the ventromedial prefrontal cortex predicted responding for still-valuable outcomes; and gray matter integrity in the premotor cortex predicted individual Pavlovian cueing effects. © 2017 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Measuring hepatic functional reserve using low temporal resolution Gd-EOB-DTPA dynamic contrast-enhanced MRI: a preliminary study comparing galactosyl human serum albumin scintigraphy with indocyanine green retention.

PubMed

Saito, Kazuhiro; Ledsam, Joseph; Sourbron, Steven; Hashimoto, Tsuyoshi; Araki, Yoichi; Akata, Soichi; Tokuuye, Koichi

2014-01-01

To investigate if tracer kinetic modelling of low temporal resolution dynamic contrast-enhanced (DCE) MRI with Gd-EOB-DTPA could replace technetium-99 m galactosyl human serum albumin (GSA) single positron emission computed tomography (SPECT) and indocyanine green (ICG) retention for the measurement of liver functional reserve. Twenty eight patients awaiting liver resection for various cancers were included in this retrospective study that was approved by the institutional review board. The Gd-EOB-DTPA MRI sequence acquired five images: unenhanced, double arterial phase, portal phase, and 4 min after injection. Intracellular contrast uptake rate (UR) and extracellular volume (Ve) were calculated from DCE-MRI, along with the ratio of GSA radioactivity of liver to heart-plus-liver and per cent of cumulative uptake from 15-16 min (LHL15 and LU15, respectively) from GSA-scintigraphy. ICG retention at 15 min, Child-Pugh cirrhosis score (CPS) and postoperative Inuyama fibrosis criteria were also recorded. Statistical analysis was with Spearman rank correlation analysis. Comparing MRI parameters with the reference methods, significant correlations were obtained for UR and LHL15, LU15, ICG15 (all 0.4-0.6, P < 0.05); UR and CPS (-0.64, P < 0.001); Ve and Inuyama (0.44, P < 0.05). Measures of liver function obtained by routine Gd-EOB-DTPA DCE-MRI with tracer kinetic modelling may provide a suitable method for the evaluation of liver functional reserve. • Magnetic resonance imaging (MRI) provides new methods of measuring hepatic functional reserve. • DCE-MRI with Gd-EOB-DTPA offers the possibility of replacing scintigraphy. • The analysis method can be used for preoperative liver function evaluation.

Toward reliable characterization of functional homogeneity in the human brain: preprocessing, scan duration, imaging resolution and computational space.

PubMed

Zuo, Xi-Nian; Xu, Ting; Jiang, Lili; Yang, Zhi; Cao, Xiao-Yan; He, Yong; Zang, Yu-Feng; Castellanos, F Xavier; Milham, Michael P

2013-01-15

While researchers have extensively characterized functional connectivity between brain regions, the characterization of functional homogeneity within a region of the brain connectome is in early stages of development. Several functional homogeneity measures were proposed previously, among which regional homogeneity (ReHo) was most widely used as a measure to characterize functional homogeneity of resting state fMRI (R-fMRI) signals within a small region (Zang et al., 2004). Despite a burgeoning literature on ReHo in the field of neuroimaging brain disorders, its test-retest (TRT) reliability remains unestablished. Using two sets of public R-fMRI TRT data, we systematically evaluated the ReHo's TRT reliability and further investigated the various factors influencing its reliability and found: 1) nuisance (head motion, white matter, and cerebrospinal fluid) correction of R-fMRI time series can significantly improve the TRT reliability of ReHo while additional removal of global brain signal reduces its reliability, 2) spatial smoothing of R-fMRI time series artificially enhances ReHo intensity and influences its reliability, 3) surface-based R-fMRI computation largely improves the TRT reliability of ReHo, 4) a scan duration of 5 min can achieve reliable estimates of ReHo, and 5) fast sampling rates of R-fMRI dramatically increase the reliability of ReHo. Inspired by these findings and seeking a highly reliable approach to exploratory analysis of the human functional connectome, we established an R-fMRI pipeline to conduct ReHo computations in both 3-dimensions (volume) and 2-dimensions (surface). Copyright © 2012 Elsevier Inc. All rights reserved.

Questions and answers on prostate multiparameter magnetic resonance imaging: Everything a urologist should know.

PubMed

Catalá, V; Salas, D; Esquena, S; Mateu, S; Algaba, F; Palou, J; de la Torre, P

2016-01-01

For many years, the detection of prostate cancer (PC) and the management of its therapy have been based primarily on prostate-specific antigen, rectal examination and prostate biopsy. However, these parameters have known limitations. Multiparametric magnetic resonance imaging (mpMRI) for prostate cancer has undergone extensive development in recent years, providing morphological and functional information. The aim of this study is to present an updated review of the scope and limitations of prostatic mpMRI for PC, in the framework of a multidisciplinary vision. We conducted a literature review (in PubMed) of articles referencing "mpMRI/staging/ PC/detection/active surveillance/therapy planning/post-therapy". We included 4 systematic reviews and other articles published in high impact-factor journals within the field of radiology and urology. MpMRI provides morphological and functional information concerning PC. This information is integrated into the Prostate Imaging Report and Date System, classifying the probability of clinically significant carcinoma on a scale from 1 to 5. The usefulness of mpMRI is currently being established for patients with high prostate-specific antigen levels and prior negative prostate biopsy; tumour staging in selected cases; assessment of patients who are candidates for active surveillance; the planning of focal treatments; and the assessment of tumour persistence and recurrence. MpMRI currently fills a relevant role in the diagnosis and therapeutic decision-making of PC. More widespread use of the technique requires a cost/benefit analysis. Copyright © 2015 AEU. Publicado por Elsevier España, S.L.U. All rights reserved.

Real-Time fMRI in Neuroscience Research and Its Use in Studying the Aging Brain

PubMed Central

Rana, Mohit; Varan, Andrew Q.; Davoudi, Anis; Cohen, Ronald A.; Sitaram, Ranganatha; Ebner, Natalie C.

2016-01-01

Cognitive decline is a major concern in the aging population. It is normative to experience some deterioration in cognitive abilities with advanced age such as related to memory performance, attention distraction to interference, task switching, and processing speed. However, intact cognitive functioning in old age is important for leading an independent day-to-day life. Thus, studying ways to counteract or delay the onset of cognitive decline in aging is crucial. The literature offers various explanations for the decline in cognitive performance in aging; among those are age-related gray and white matter atrophy, synaptic degeneration, blood flow reduction, neurochemical alterations, and change in connectivity patterns with advanced age. An emerging literature on neurofeedback and Brain Computer Interface (BCI) reports exciting results supporting the benefits of volitional modulation of brain activity on cognition and behavior. Neurofeedback studies based on real-time functional magnetic resonance imaging (rtfMRI) have shown behavioral changes in schizophrenia and behavioral benefits in nicotine addiction. This article integrates research on cognitive and brain aging with evidence of brain and behavioral modification due to rtfMRI neurofeedback. We offer a state-of-the-art description of the rtfMRI technique with an eye towards its application in aging. We present preliminary results of a feasibility study exploring the possibility of using rtfMRI to train older adults to volitionally control brain activity. Based on these first findings, we discuss possible implementations of rtfMRI neurofeedback as a novel technique to study and alleviate cognitive decline in healthy and pathological aging. PMID:27803662

Development of an apparatus and methodology for conducting functional magnetic resonance imaging (fMRI) with pharmacological stimuli in conscious rhesus monkeys.

PubMed

Murnane, Kevin Sean; Howell, Leonard Lee

2010-08-15

Functional magnetic resonance imaging (fMRI) is a technique with significant potential to advance our understanding of multiple brain systems. However, when human subjects undergo fMRI studies they are typically conscious whereas pre-clinical fMRI studies typically utilize anesthesia, which complicates comparisons across studies. Therefore, we have developed an apparatus suitable for imaging conscious rhesus monkeys. In order to minimize subject stress and spatial motion, each subject was acclimated to the necessary procedures over several months. The effectiveness of this process was then evaluated, in fully trained subjects, by quantifying objective physiological measures. These physiological metrics were stable both within and across sessions and did not differ from when these same subjects were immobilized using standard primate handling procedures. Subject motion and blood oxygenation level dependent (BOLD) fMRI measurements were then evaluated by scanning subjects under three different conditions: the absence of stimulation, presentation of a visual stimulus, or administration of intravenous (i.v.) cocaine (0.3mg/kg). Spatial motion differed neither by condition nor along the three principal axes. In addition, maximum translational and rotational motion never exceeded one half of the voxel size (0.75 mm) or 1.5 degrees, respectively. Furthermore, the localization of changes in blood oxygenation closely matched those reported in previous studies using similar stimuli. These findings document the feasibility of fMRI data collection in conscious rhesus monkeys using these procedures and allow for the further study of the neural effects of psychoactive drugs. (c) 2010 Elsevier B.V. All rights reserved.

Novel magnetomechanical MR compatible vibrational device for producing kinesthetic illusion during fMRI.

PubMed

Carr, Sarah J; Borreggine, Kristin; Heilman, Jeremiah; Griswold, Mark; Walter, Benjamin L

2013-11-01

Functional MRI (fMRI) can provide insights into the functioning of the sensorimotor system, which is of particular interest in studying people with movement disorders or chronic pain conditions. This creates a demand for manipulanda that can fit and operate within the environment of a MRI scanner. Here, the authors present a magnetomechanical device that delivers a vibrotactile sensation to the skin with a force of approximately 9 N. MRI compatibility of the device was tested in a 3 T scanner using a phantom to simulate the head. Preliminary investigation into the effectiveness of the device at producing cortical and subcortical activity was also conducted with a group of seven healthy subjects. The vibration was applied to the right extensor carpi ulnaris tendon to induce a kinesthetic illusion of flexion and extension of the wrist. The MRI compatibility tests showed the device did not produce image artifacts and the generated electromagnetic field did not disrupt the static magnetic field of the scanner or its operation. The subject group results showed activity in the contralateral putamen, premotor cortex, and dorsal lateral prefrontal cortex. Ipsilaterally, there was increased activity in the superior and inferior parietal lobules. Areas that activated bilaterally included the thalamus, anterior cingulate, secondary somatosensory areas (S2), temporal lobes, and visual association areas. This device offers an effective tool with precise control over the vibratory stimulus, delivering higher forces than some other types of devices (e.g., piezoelectric actuators). It can be useful for investigating sensory systems and sensorimotor integration.

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.

A phenome-wide examination of neural and cognitive function.

PubMed

Poldrack, R A; Congdon, E; Triplett, W; Gorgolewski, K J; Karlsgodt, K H; Mumford, J A; Sabb, F W; Freimer, N B; London, E D; Cannon, T D; Bilder, R M

2016-12-06

This data descriptor outlines a shared neuroimaging dataset from the UCLA Consortium for Neuropsychiatric Phenomics, which focused on understanding the dimensional structure of memory and cognitive control (response inhibition) functions in both healthy individuals (130 subjects) and individuals with neuropsychiatric disorders including schizophrenia (50 subjects), bipolar disorder (49 subjects), and attention deficit/hyperactivity disorder (43 subjects). The dataset includes an extensive set of task-based fMRI assessments, resting fMRI, structural MRI, and high angular resolution diffusion MRI. The dataset is shared through the OpenfMRI project, and is formatted according to the Brain Imaging Data Structure (BIDS) standard.

In vivo Visuotopic Brain Mapping with Manganese-Enhanced MRI and Resting-State Functional Connectivity MRI

PubMed Central

Chan, Kevin C.; Fan, Shu-Juan; Chan, Russell W.; Cheng, Joe S.; Zhou, Iris Y.; Wu, Ed X.

2014-01-01

The rodents are an increasingly important model for understanding the mechanisms of development, plasticity, functional specialization and disease in the visual system. However, limited tools have been available for assessing the structural and functional connectivity of the visual brain network globally, in vivo and longitudinally. There are also ongoing debates on whether functional brain connectivity directly reflects structural brain connectivity. In this study, we explored the feasibility of manganese-enhanced MRI (MEMRI) via 3 different routes of Mn2+ administration for visuotopic brain mapping and understanding of physiological transport in normal and visually deprived adult rats. In addition, resting-state functional connectivity MRI (RSfcMRI) was performed to evaluate the intrinsic functional network and structural-functional relationships in the corresponding anatomical visual brain connections traced by MEMRI. Upon intravitreal, subcortical, and intracortical Mn2+ injection, different topographic and layer-specific Mn enhancement patterns could be revealed in the visual cortex and subcortical visual nuclei along retinal, callosal, cortico-subcortical, transsynaptic and intracortical horizontal connections. Loss of visual input upon monocular enucleation to adult rats appeared to reduce interhemispheric polysynaptic Mn2+ transfer but not intra- or inter-hemispheric monosynaptic Mn2+ transport after Mn2+ injection into visual cortex. In normal adults, both structural and functional connectivity by MEMRI and RSfcMRI was stronger interhemispherically between bilateral primary/secondary visual cortex (V1/V2) transition zones (TZ) than between V1/V2 TZ and other cortical nuclei. Intrahemispherically, structural and functional connectivity was stronger between visual cortex and subcortical visual nuclei than between visual cortex and other subcortical nuclei. The current results demonstrated the sensitivity of MEMRI and RSfcMRI for assessing the neuroarchitecture, neurophysiology and structural-functional relationships of the visual brains in vivo. These may possess great potentials for effective monitoring and understanding of the basic anatomical and functional connections in the visual system during development, plasticity, disease, pharmacological interventions and genetic modifications in future studies. PMID:24394694

Advanced magnetic resonance imaging in glioblastoma: a review.

PubMed

Shukla, Gaurav; Alexander, Gregory S; Bakas, Spyridon; Nikam, Rahul; Talekar, Kiran; Palmer, Joshua D; Shi, Wenyin

2017-08-01

Glioblastoma, the most common and most rapidly progressing primary malignant tumor of the central nervous system, continues to portend a dismal prognosis, despite improvements in diagnostic and therapeutic strategies over the last 20 years. The standard of care radiographic characterization of glioblastoma is magnetic resonance imaging (MRI), which is a widely utilized examination in the diagnosis and post-treatment management of patients with glioblastoma. Basic MRI modalities available from any clinical scanner, including native T1-weighted (T1w) and contrast-enhanced (T1CE), T2-weighted (T2w), and T2-fluid-attenuated inversion recovery (T2-FLAIR) sequences, provide critical clinical information about various processes in the tumor environment. In the last decade, advanced MRI modalities are increasingly utilized to further characterize glioblastomas more comprehensively. These include multi-parametric MRI sequences, such as dynamic susceptibility contrast (DSC), dynamic contrast enhancement (DCE), higher order diffusion techniques such as diffusion tensor imaging (DTI), and MR spectroscopy (MRS). Significant efforts are ongoing to implement these advanced imaging modalities into improved clinical workflows and personalized therapy approaches. Functional MRI (fMRI) and tractography are increasingly being used to identify eloquent cortices and important tracts to minimize postsurgical neuro-deficits. A contemporary review of the application of standard and advanced MRI in clinical neuro-oncologic practice is presented here.

Clinical applications of the functional connectome

PubMed Central

Castellanos, F. Xavier; Di Martino, Adriana; Craddock, R. Cameron; Mehta, Ashesh D.; Milham, Michael P.

2013-01-01

Central to the development of clinical applications of functional connectomics for neurology and psychiatry is the discovery and validation of biomarkers. Resting state fMRI (R-fMRI) is emerging as a mainstream approach for imaging-based biomarker identification, detecting variations in the functional connectome that can be attributed to clinical variables (e.g., diagnostic status). Despite growing enthusiasm, many challenges remain. Here, we assess evidence of the readiness of R-fMRI based functional connectomics to lead to clinically meaningful biomarker identification through the lens of the criteria used to evaluate clinical tests (i.e., validity, reliability, sensitivity, specificity, and applicability). We focus on current R-fMRI-based prediction efforts, and survey R-fMRI used for neurosurgical planning. We identify gaps and needs for R-fMRI-based biomarker identification, highlighting the potential of emerging conceptual, analytical and cultural innovations (e.g., the Research Domain Criteria Project (RDoC), open science initiatives, and Big Data) to address them. Additionally, we note the need to expand future efforts beyond identification of biomarkers for disease status alone to include clinical variables related to risk, expected treatment response and prognosis. PMID:23631991

DPARSF: A MATLAB Toolbox for "Pipeline" Data Analysis of Resting-State fMRI.

PubMed

Chao-Gan, Yan; Yu-Feng, Zang

2010-01-01

Resting-state functional magnetic resonance imaging (fMRI) has attracted more and more attention because of its effectiveness, simplicity and non-invasiveness in exploration of the intrinsic functional architecture of the human brain. However, user-friendly toolbox for "pipeline" data analysis of resting-state fMRI is still lacking. Based on some functions in Statistical Parametric Mapping (SPM) and Resting-State fMRI Data Analysis Toolkit (REST), we have developed a MATLAB toolbox called Data Processing Assistant for Resting-State fMRI (DPARSF) for "pipeline" data analysis of resting-state fMRI. After the user arranges the Digital Imaging and Communications in Medicine (DICOM) files and click a few buttons to set parameters, DPARSF will then give all the preprocessed (slice timing, realign, normalize, smooth) data and results for functional connectivity, regional homogeneity, amplitude of low-frequency fluctuation (ALFF), and fractional ALFF. DPARSF can also create a report for excluding subjects with excessive head motion and generate a set of pictures for easily checking the effect of normalization. In addition, users can also use DPARSF to extract time courses from regions of interest.

Correlation of the CT Compatible Stereotaxic Craniotomy with MRI Scans of the Patients for Removing Cranial Lesions Located Eloquent Areas and Deep Sites of Brain.

PubMed

Gulsen, Salih

2015-03-15

The first goal in neurosurgery is to protect neural function as long as it is possible. Moreover, while protecting the neural function, a neurosurgeon should extract the maximum amount of tumoral tissue from the tumour region of the brain. So neurosurgery and technological advancement go hand in hand to realize this goal. Using of CT compatible stereotaxy for removing a cranial tumour is to be commended as a cornerstone of these technological advancements. Following CT compatible stereotaxic system applications in neurosurgery, different techniques have taken place in neurosurgical practice. These techniques are magnetic resonance imaging (MRI), MRI compatible stereotaxis, frameless stereotaxy, volumetric stereotaxy, functional MRI, diffusion tensor (DT) imaging techniques (tractography of the white matter), intraoperative MRI and neuronavigation systems. However, to use all of this equipment having these technologies would be impossible because of economic reasons. However, when we correlated this technique with MRI scans of the patients with CT compatible stereotaxy scans, it is possible to provide gross total resection and protect and improve patients' neural functions.

Analyzing and Assessing Brain Structure with Graph Connectivity Measures

DTIC Science & Technology

2014-05-09

structural brain networks, i.e. determining which regions of the brain are physically connected. Meanwhile, functional MRI ( fMRI ) yields an image of...produced by fMRI is a map of which parts are of the brain are active and which are not at a given time. In creating functional networks, regions of...the brain which often activitate together, i.e., often show up on fMRI as deoxygenated regions together, are considered connected. DTI allows the

Defining Functional Areas in Individual Human Brains using Resting Functional Connectivity MRI

PubMed Central

Cohen, Alexander L.; Fair, Damien A.; Dosenbach, Nico U.F.; Miezin, Francis M.; Dierker, Donna; Van Essen, David C.; Schlaggar, Bradley L.; Petersen, Steven E.

2009-01-01

The cerebral cortex is anatomically organized at many physical scales starting at the level of single neurons and extending up to functional systems. Current functional magnetic resonance imaging (fMRI) studies often focus at the level of areas, networks, and systems. Except in restricted domains, (e.g. topographically-organized sensory regions), it is difficult to determine area boundaries in the human brain using fMRI. The ability to delineate functional areas non-invasively would enhance the quality of many experimental analyses allowing more accurate across-subject comparisons of independently identified functional areas. Correlations in spontaneous BOLD activity, often referred to as resting state functional connectivity (rs-fcMRI), are especially promising as a way to accurately localize differences in patterns of correlated activity across large expanses of cortex. In the current report, we applied a novel set of image analysis tools to explore the utility of rs-fcMRI for defining wide-ranging functional area boundaries. We find that rs-fcMRI patterns show sharp transitions in correlation patterns and that these putative areal boundaries can be reliably detected in individual subjects as well as in group data. Additionally, combining surface-based analysis techniques with image processing algorithms allows automated mapping of putative areal boundaries across large expanses of cortex without the need for prior information about a region’s function or topography. Our approach reliably produces maps of bounded regions appropriate in size and number for putative functional areas. These findings will hopefully stimulate further methodological refinements and validations. PMID:18367410

Intrinsic, stimulus-driven and task-dependent connectivity in human auditory cortex.

PubMed

Häkkinen, Suvi; Rinne, Teemu

2018-06-01

A hierarchical and modular organization is a central hypothesis in the current primate model of auditory cortex (AC) but lacks validation in humans. Here we investigated whether fMRI connectivity at rest and during active tasks is informative of the functional organization of human AC. Identical pitch-varying sounds were presented during a visual discrimination (i.e. no directed auditory attention), pitch discrimination, and two versions of pitch n-back memory tasks. Analysis based on fMRI connectivity at rest revealed a network structure consisting of six modules in supratemporal plane (STP), temporal lobe, and inferior parietal lobule (IPL) in both hemispheres. In line with the primate model, in which higher-order regions have more longer-range connections than primary regions, areas encircling the STP module showed the highest inter-modular connectivity. Multivariate pattern analysis indicated significant connectivity differences between the visual task and rest (driven by the presentation of sounds during the visual task), between auditory and visual tasks, and between pitch discrimination and pitch n-back tasks. Further analyses showed that these differences were particularly due to connectivity modulations between the STP and IPL modules. While the results are generally in line with the primate model, they highlight the important role of human IPL during the processing of both task-irrelevant and task-relevant auditory information. Importantly, the present study shows that fMRI connectivity at rest, during presentation of sounds, and during active listening provides novel information about the functional organization of human AC.

Pancreatic Neuroendocrine Tumor with Atypical Radiologic Presentation.

PubMed

Singh, Ramandeep; Calhoun, Sean; Shin, Minchul; Katz, Robert

2008-01-01

An atypical radiographic presentation of a rare non-functional pancreatic neuroendocrine tumor as seen on US, CT and MRI is described. Radiographic-pathologic correlation via gross autopsy specimens and immuno-histochemical staining demonstrates the pancreas to be markedly enlarged with extensive calcifications and numerous tiny cysts secondary to diffuse neoplastic infiltration without a focal mass.

Addiction Related Alteration in Resting-state Brain Connectivity

PubMed Central

Ma, Ning; Liu, Ying; Li, Nan; Wang, Chang-Xin; Zhang, Hao; Jiang, Xiao-Feng; Xu, Hu-Sheng; Fu, Xian-Ming; Hu, Xiaoping; Zhang, Da-Ren

2009-01-01

It is widely accepted that addictive drug use is related to abnormal functional organization in the user’s brain. The present study aimed to identify this type of abnormality within the brain networks implicated in addiction by resting-state functional connectivity measured with functional magnetic resonance imaging (fMRI). With fMRI data acquired during resting state from 14 chronic heroin users (12 of whom were being treated with methadone) and 13 non-addicted controls, we investigated the addiction related alteration in functional connectivity between the regions in the circuits implicated in addiction with seed-based correlation analysis. Compared with controls, chronic heroin users showed increased functional connectivity between nucleus accumbens and ventral/rostral anterior cingulate cortex (ACC), and orbital frontal cortex (OFC), between amygdala and OFC; and reduced functional connectivity between prefrontal cortex and OFC, and ACC. These observations of altered resting-state functional connectivity suggested abnormal functional organization in the addicted brain and may provide additional evidence supporting the theory of addiction that emphasizes enhanced salience value of a drug and its related cues but weakened cognitive control in the addictive state. PMID:19703568

Altered resting brain function and structure in professional badminton players.

PubMed

Di, Xin; Zhu, Senhua; Jin, Hua; Wang, Pin; Ye, Zhuoer; Zhou, Ke; Zhuo, Yan; Rao, Hengyi

2012-01-01

Neuroimaging studies of professional athletic or musical training have demonstrated considerable practice-dependent plasticity in various brain structures, which may reflect distinct training demands. In the present study, structural and functional brain alterations were examined in professional badminton players and compared with healthy controls using magnetic resonance imaging (MRI) and resting-state functional MRI. Gray matter concentration (GMC) was assessed using voxel-based morphometry (VBM), and resting-brain functions were measured by amplitude of low-frequency fluctuation (ALFF) and seed-based functional connectivity. Results showed that the athlete group had greater GMC and ALFF in the right and medial cerebellar regions, respectively. The athlete group also demonstrated smaller ALFF in the left superior parietal lobule and altered functional connectivity between the left superior parietal and frontal regions. These findings indicate that badminton expertise is associated with not only plastic structural changes in terms of enlarged gray matter density in the cerebellum, but also functional alterations in fronto-parietal connectivity. Such structural and functional alterations may reflect specific experiences of badminton training and practice, including high-capacity visuo-spatial processing and hand-eye coordination in addition to refined motor skills.

Low-Cost High-Performance MRI

NASA Astrophysics Data System (ADS)

Sarracanie, Mathieu; Lapierre, Cristen D.; Salameh, Najat; Waddington, David E. J.; Witzel, Thomas; Rosen, Matthew S.

2015-10-01

Magnetic Resonance Imaging (MRI) is unparalleled in its ability to visualize anatomical structure and function non-invasively with high spatial and temporal resolution. Yet to overcome the low sensitivity inherent in inductive detection of weakly polarized nuclear spins, the vast majority of clinical MRI scanners employ superconducting magnets producing very high magnetic fields. Commonly found at 1.5-3 tesla (T), these powerful magnets are massive and have very strict infrastructure demands that preclude operation in many environments. MRI scanners are costly to purchase, site, and maintain, with the purchase price approaching $1 M per tesla (T) of magnetic field. We present here a remarkably simple, non-cryogenic approach to high-performance human MRI at ultra-low magnetic field, whereby modern under-sampling strategies are combined with fully-refocused dynamic spin control using steady-state free precession techniques. At 6.5 mT (more than 450 times lower than clinical MRI scanners) we demonstrate (2.5 × 3.5 × 8.5) mm3 imaging resolution in the living human brain using a simple, open-geometry electromagnet, with 3D image acquisition over the entire brain in 6 minutes. We contend that these practical ultra-low magnetic field implementations of MRI (<10 mT) will complement traditional MRI, providing clinically relevant images and setting new standards for affordable (<$50,000) and robust portable devices.

A new concept of a unified parameter management, experiment control, and data analysis in fMRI: application to real-time fMRI at 3T and 7T.

PubMed

Hollmann, M; Mönch, T; Mulla-Osman, S; Tempelmann, C; Stadler, J; Bernarding, J

2008-10-30

In functional MRI (fMRI) complex experiments and applications require increasingly complex parameter handling as the experimental setup usually consists of separated soft- and hardware systems. Advanced real-time applications such as neurofeedback-based training or brain computer interfaces (BCIs) may even require adaptive changes of the paradigms and experimental setup during the measurement. This would be facilitated by an automated management of the overall workflow and a control of the communication between all experimental components. We realized a concept based on an XML software framework called Experiment Description Language (EDL). All parameters relevant for real-time data acquisition, real-time fMRI (rtfMRI) statistical data analysis, stimulus presentation, and activation processing are stored in one central EDL file, and processed during the experiment. A usability study comparing the central EDL parameter management with traditional approaches showed an improvement of the complete experimental handling. Based on this concept, a feasibility study realizing a dynamic rtfMRI-based brain computer interface showed that the developed system in combination with EDL was able to reliably detect and evaluate activation patterns in real-time. The implementation of a centrally controlled communication between the subsystems involved in the rtfMRI experiments reduced potential inconsistencies, and will open new applications for adaptive BCIs.

A three-way parallel ICA approach to analyze links among genetics, brain structure and brain function.

PubMed

Vergara, Victor M; Ulloa, Alvaro; Calhoun, Vince D; Boutte, David; Chen, Jiayu; Liu, Jingyu

2014-09-01

Multi-modal data analysis techniques, such as the Parallel Independent Component Analysis (pICA), are essential in neuroscience, medical imaging and genetic studies. The pICA algorithm allows the simultaneous decomposition of up to two data modalities achieving better performance than separate ICA decompositions and enabling the discovery of links between modalities. However, advances in data acquisition techniques facilitate the collection of more than two data modalities from each subject. Examples of commonly measured modalities include genetic information, structural magnetic resonance imaging (MRI) and functional MRI. In order to take full advantage of the available data, this work extends the pICA approach to incorporate three modalities in one comprehensive analysis. Simulations demonstrate the three-way pICA performance in identifying pairwise links between modalities and estimating independent components which more closely resemble the true sources than components found by pICA or separate ICA analyses. In addition, the three-way pICA algorithm is applied to real experimental data obtained from a study that investigate genetic effects on alcohol dependence. Considered data modalities include functional MRI (contrast images during alcohol exposure paradigm), gray matter concentration images from structural MRI and genetic single nucleotide polymorphism (SNP). The three-way pICA approach identified links between a SNP component (pointing to brain function and mental disorder associated genes, including BDNF, GRIN2B and NRG1), a functional component related to increased activation in the precuneus area, and a gray matter component comprising part of the default mode network and the caudate. Although such findings need further verification, the simulation and in-vivo results validate the three-way pICA algorithm presented here as a useful tool in biomedical data fusion applications. Copyright © 2014 Elsevier Inc. All rights reserved.

Evaluation of MRI issues for an access port with a radiofrequency identification (RFID) tag.

PubMed

Titterington, Blake; Shellock, Frank G

2013-10-01

A medical implant that contains metal, such as an RFID tag, must undergo proper MRI testing to ensure patient safety and to determine that the function of the RFID tag is not compromised by exposure to MRI conditions. Therefore, the objective of this investigation was to assess MRI issues for a new access port that incorporates an RFID tag. Samples of the access port with an RFID tag (Medcomp Power Injectable Port with CertainID; Medcomp, Harleysville, PA) were evaluated using standard protocols to assess magnetic field interactions (translational attraction and torque; 3-T), MRI-related heating (3-T), artifacts (3-T), and functional changes associated with different MRI conditions (nine samples, exposed to different MRI conditions at 1.5-T and 3-T). Magnetic field interactions were not substantial and will pose no hazards to patients. MRI-related heating was minimal (highest temperature change, 1.7°C; background temperature rise, 1.6°C). Artifacts were moderate in size in relation to the device. Exposures to MRI conditions at 1.5-T and 3-T did not alter or damage the functional aspects of the RFID tag. Based on the findings of the test, this new access port with an RFID tag is acceptable (or, MR conditional, using current MRI labeling terminology) for patients undergoing MRI examinations at 1.5-T/64-MHz and 3-T/128-MHz. Copyright © 2013 Elsevier Inc. All rights reserved.

State-space model with deep learning for functional dynamics estimation in resting-state fMRI.

PubMed

Suk, Heung-Il; Wee, Chong-Yaw; Lee, Seong-Whan; Shen, Dinggang

2016-04-01

Studies on resting-state functional Magnetic Resonance Imaging (rs-fMRI) have shown that different brain regions still actively interact with each other while a subject is at rest, and such functional interaction is not stationary but changes over time. In terms of a large-scale brain network, in this paper, we focus on time-varying patterns of functional networks, i.e., functional dynamics, inherent in rs-fMRI, which is one of the emerging issues along with the network modelling. Specifically, we propose a novel methodological architecture that combines deep learning and state-space modelling, and apply it to rs-fMRI based Mild Cognitive Impairment (MCI) diagnosis. We first devise a Deep Auto-Encoder (DAE) to discover hierarchical non-linear functional relations among regions, by which we transform the regional features into an embedding space, whose bases are complex functional networks. Given the embedded functional features, we then use a Hidden Markov Model (HMM) to estimate dynamic characteristics of functional networks inherent in rs-fMRI via internal states, which are unobservable but can be inferred from observations statistically. By building a generative model with an HMM, we estimate the likelihood of the input features of rs-fMRI as belonging to the corresponding status, i.e., MCI or normal healthy control, based on which we identify the clinical label of a testing subject. In order to validate the effectiveness of the proposed method, we performed experiments on two different datasets and compared with state-of-the-art methods in the literature. We also analyzed the functional networks learned by DAE, estimated the functional connectivities by decoding hidden states in HMM, and investigated the estimated functional connectivities by means of a graph-theoretic approach. Copyright © 2016 Elsevier Inc. All rights reserved.

State-space model with deep learning for functional dynamics estimation in resting-state fMRI

PubMed Central

Suk, Heung-Il; Wee, Chong-Yaw; Lee, Seong-Whan; Shen, Dinggang

2017-01-01

Studies on resting-state functional Magnetic Resonance Imaging (rs-fMRI) have shown that different brain regions still actively interact with each other while a subject is at rest, and such functional interaction is not stationary but changes over time. In terms of a large-scale brain network, in this paper, we focus on time-varying patterns of functional networks, i.e., functional dynamics, inherent in rs-fMRI, which is one of the emerging issues along with the network modelling. Specifically, we propose a novel methodological architecture that combines deep learning and state-space modelling, and apply it to rs-fMRI based Mild Cognitive Impairment (MCI) diagnosis. We first devise a Deep Auto-Encoder (DAE) to discover hierarchical non-linear functional relations among regions, by which we transform the regional features into an embedding space, whose bases are complex functional networks. Given the embedded functional features, we then use a Hidden Markov Model (HMM) to estimate dynamic characteristics of functional networks inherent in rs-fMRI via internal states, which are unobservable but can be inferred from observations statistically. By building a generative model with an HMM, we estimate the likelihood of the input features of rs-fMRI as belonging to the corresponding status, i.e., MCI or normal healthy control, based on which we identify the clinical label of a testing subject. In order to validate the effectiveness of the proposed method, we performed experiments on two different datasets and compared with state-of-the-art methods in the literature. We also analyzed the functional networks learned by DAE, estimated the functional connectivities by decoding hidden states in HMM, and investigated the estimated functional connectivities by means of a graph-theoretic approach. PMID:26774612

Computer-aided Detection of Prostate Cancer with MRI: Technology and Applications.

PubMed

Liu, Lizhi; Tian, Zhiqiang; Zhang, Zhenfeng; Fei, Baowei

2016-08-01

One in six men will develop prostate cancer in his lifetime. Early detection and accurate diagnosis of the disease can improve cancer survival and reduce treatment costs. Recently, imaging of prostate cancer has greatly advanced since the introduction of multiparametric magnetic resonance imaging (mp-MRI). Mp-MRI consists of T2-weighted sequences combined with functional sequences including dynamic contrast-enhanced MRI, diffusion-weighted MRI, and magnetic resonance spectroscopy imaging. Because of the big data and variations in imaging sequences, detection can be affected by multiple factors such as observer variability and visibility and complexity of the lesions. To improve quantitative assessment of the disease, various computer-aided detection systems have been designed to help radiologists in their clinical practice. This review paper presents an overview of literatures on computer-aided detection of prostate cancer with mp-MRI, which include the technology and its applications. The aim of the survey is threefold: an introduction for those new to the field, an overview for those working in the field, and a reference for those searching for literature on a specific application. Copyright © 2016 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Functional MRI detects perfusion impairment in renal allografts with delayed graft function.

PubMed

Hueper, Katja; Gueler, Faikah; Bräsen, Jan Hinrich; Gutberlet, Marcel; Jang, Mi-Sun; Lehner, Frank; Richter, Nicolas; Hanke, Nils; Peperhove, Matti; Martirosian, Petros; Tewes, Susanne; Vo Chieu, Van Dai; Großhennig, Anika; Haller, Hermann; Wacker, Frank; Gwinner, Wilfried; Hartung, Dagmar

2015-06-15

Delayed graft function (DGF) after kidney transplantation is not uncommon, and it is associated with long-term allograft impairment. Our aim was to compare renal perfusion changes measured with noninvasive functional MRI in patients early after kidney transplantation to renal function and allograft histology in biopsy samples. Forty-six patients underwent MRI 4-11 days after transplantation. Contrast-free MRI renal perfusion images were acquired using an arterial spin labeling technique. Renal function was assessed by estimated glomerular filtration rate (eGFR), and renal biopsies were performed when indicated within 5 days of MRI. Twenty-six of 46 patients had DGF. Of these, nine patients had acute rejection (including borderline), and eight had other changes (e.g., tubular injury or glomerulosclerosis). Renal perfusion was significantly lower in the DGF group compared with the group with good allograft function (231 ± 15 vs. 331 ± 15 ml·min(-1)·100 g(-1), P < 0.001). Living donor allografts exhibited significantly higher perfusion values compared with deceased donor allografts (P < 0.001). Renal perfusion significantly correlated with eGFR (r = 0.64, P < 0.001), resistance index (r = -0.57, P < 0.001), and cold ischemia time (r = -0.48, P < 0.01). Furthermore, renal perfusion impairment early after transplantation predicted inferior renal outcome and graft loss. In conclusion, noninvasive functional MRI detects renal perfusion impairment early after kidney transplantation in patients with DGF. Copyright © 2015 the American Physiological Society.

Hyperpolarized (3)He magnetic resonance imaging: comparison with four-dimensional x-ray computed tomography imaging in lung cancer.

PubMed

Mathew, Lindsay; Wheatley, Andrew; Castillo, Richard; Castillo, Edward; Rodrigues, George; Guerrero, Thomas; Parraga, Grace

2012-12-01

Pulmonary functional imaging using four-dimensional x-ray computed tomographic (4DCT) imaging and hyperpolarized (3)He magnetic resonance imaging (MRI) provides regional lung function estimates in patients with lung cancer in whom pulmonary function measurements are typically dominated by tumor burden. The aim of this study was to evaluate the quantitative spatial relationship between 4DCT and hyperpolarized (3)He MRI ventilation maps. Eleven patients with lung cancer provided written informed consent to 4DCT imaging and MRI performed within 11 ± 14 days. Hyperpolarized (3)He MRI was acquired in breath-hold after inhalation from functional residual capacity of 1 L hyperpolarized (3)He, whereas 4DCT imaging was acquired over a single tidal breath of room air. For hyperpolarized (3)He MRI, the percentage ventilated volume was generated using semiautomated segmentation; for 4DCT imaging, pulmonary function maps were generated using the correspondence between identical tissue elements at inspiratory and expiratory phases to generate percentage ventilated volume. After accounting for differences in image acquisition lung volumes ((3)He MRI: 1.9 ± 0.5 L ipsilateral, 2.3 ± 0.7 L contralateral; 4DCT imaging: 1.2 ± 0.3 L ipsilateral, 1.3 ± 0.4 L contralateral), there was no significant difference in percentage ventilated volume between hyperpolarized (3)He MRI (72 ± 11% ipsilateral, 79 ± 12% contralateral) and 4DCT imaging (74 ± 3% ipsilateral, 75 ± 4% contralateral). Spatial correspondence between 4DCT and (3)He MRI ventilation was evaluated using the Dice similarity coefficient index (ipsilateral, 86 ± 12%; contralateral, 88 ± 12%). Despite rather large differences in image acquisition breathing maneuvers, good spatial and significant quantitative agreement was observed for ventilation maps on hyperpolarized (3)He MRI and 4DCT imaging, suggesting that pulmonary regions with good lung function are similar between modalities in this small group of patients with lung cancer. Copyright © 2012 AUR. Published by Elsevier Inc. All rights reserved.

Tractography-Based Score for Learning Effective Connectivity From Multimodal Imaging Data Using Dynamic Bayesian Networks.

PubMed

Dang, Shilpa; Chaudhury, Santanu; Lall, Brejesh; Roy, Prasun K

2018-05-01

Effective connectivity (EC) is the methodology for determining functional-integration among the functionally active segregated regions of the brain. By definition EC is "the causal influence exerted by one neuronal group on another" which is constrained by anatomical connectivity (AC) (axonal connections). AC is necessary for EC but does not fully determine it, because synaptic communication occurs dynamically in a context-dependent fashion. Although there is a vast emerging evidence of structure-function relationship using multimodal imaging studies, till date only a few studies have done joint modeling of the two modalities: functional MRI (fMRI) and diffusion tensor imaging (DTI). We aim to propose a unified probabilistic framework that combines information from both sources to learn EC using dynamic Bayesian networks (DBNs). DBNs are probabilistic graphical temporal models that learn EC in an exploratory fashion. Specifically, we propose a novel anatomically informed (AI) score that evaluates fitness of a given connectivity structure to both DTI and fMRI data simultaneously. The AI score is employed in structure learning of DBN given the data. Experiments with synthetic-data demonstrate the face validity of structure learning with our AI score over anatomically uninformed counterpart. Moreover, real-data results are cross-validated by performing classification-experiments. EC inferred on real fMRI-DTI datasets is found to be consistent with previous literature and show promising results in light of the AC present as compared to other classically used techniques such as Granger-causality. Multimodal analyses provide a more reliable basis for differentiating brain under abnormal/diseased conditions than the single modality analysis.

Developing easy to perform routine MRI measurements as potential surrogates for cognitive impairment in MS.

PubMed

Morrow, Sarah A; Menon, Suresh; Rosehart, Heather; Sharma, Manas

2017-02-01

One of the most frequently disabling symptoms in Multiple Sclerosis (MS) is cognitive impairment which is often insidious in onset and therefore difficult to recognize in the early stages, for both persons with MS and clinicians. A biomarker that would help identify those at risk of cognitive impairment, or with only mild impairment, would be a useful tool for clinicians. Using MRI, already an integral tool in the diagnosis and monitoring of disease activity in MS, would be ideal. Thus, this study aimed to determine if simple measures on routine MRI could serve as potential biomarkers for cognitive impairment in MS. We retrospectively identified 51 persons with MS who had a cognitive assessment and MRI within six months of the MRI. Simple linear measurements of the hippocampi, bifrontral and third ventricular width, bicaudate width and the anterior, mid and posterior corpus callosum were made. Pearson's correlations examined the relationship between these MRI measures and cognitive tests, and MRI measures were compared in persons with MS who were either normal or cognitively impaired on objective cognitive tests using Analysis of Covariance (ANCOVA). Bicaudate span and third ventricular width were both negatively correlated, while corpus callosal measures were positive correlated with cognitive test performance. After controlling for potential confounders, bicaudate span was significant different on measures of immediate recall. Both anterior and posterior corpus collosal measure were significantly different on measures of verbal fluency, immediate recall and higher executive function; while the anterior corpus callosum was also significantly different on processing speed. The middle corpus collosal measure was significantly different on immediate recall and higher executive function. This study presents data demonstrating that simple to apply MRI measures of atrophy may serve as biomarkers for cognitive impairment in persons with MS. Further prospective studies are needed to validate these findings. Copyright © 2016 Elsevier B.V. All rights reserved.

Changes in Male Rat Sexual Behavior and Brain Activity Revealed by Functional Magnetic Resonance Imaging in Response to Chronic Mild Stress.

PubMed

Chen, Guotao; Yang, Baibing; Chen, Jianhuai; Zhu, Leilei; Jiang, Hesong; Yu, Wen; Zang, Fengchao; Chen, Yun; Dai, Yutian

2018-02-01

Non-organic erectile dysfunction (noED) at functional imaging has been related to abnormal brain activity and requires animal models for further research on the associated molecular mechanisms. To develop a noED animal model based on chronic mild stress and investigate brain activity changes. We used 6 weeks of chronic mild stress to induce depression. The sucrose consumption test was used to assess the hedonic state. The apomorphine test and sexual behavior test were used to select male rats with ED. Rats with depression and ED were considered to have noED. Blood oxygen level-dependent-based resting-state functional magnetic resonance imaging (fMRI) studies were conducted on these rats, and the amplitude of low-frequency fluctuations and functional connectivity were analyzed to determine brain activity changes. The sexual behavior test and resting-state fMRI were used for outcome measures. The induction of depression was confirmed by the sucrose consumption test. A low intromission ratio and increased mount and intromission latencies were observed in male rats with depression. No erection was observed in male rats with depression during the apomorphine test. Male rats with depression and ED were considered to have noED. The possible central pathologic mechanism shown by fMRI involved the amygdaloid body, dorsal thalamus, hypothalamus, caudate-putamen, cingulate gyrus, insular cortex, visual cortex, sensory cortex, motor cortex, and cerebellum. Similar findings have been found in humans. The present study provided a novel noED rat model for further research on the central mechanism of noED. The present study developed a novel noED rat model and analyzed brain activity changes based at fMRI. The observed brain activity alterations might not extend to humans. The present study developed a novel noED rat model with brain activity alterations related to sexual arousal and erection, which will be helpful for further research involving the central mechanism of noED. Chen G, Yang B, Chen J, et al. Changes in Male Rat Sexual Behavior and Brain Activity Revealed by Functional Magnetic Resonance Imaging in Response to Chronic Mild Stress. J Sex Med 2018;15:136-147. Copyright © 2017 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.

Tracking brain arousal fluctuations with fMRI

PubMed Central

Chang, Catie; Leopold, David A.; Schölvinck, Marieke Louise; Mandelkow, Hendrik; Picchioni, Dante; Liu, Xiao; Ye, Frank Q.; Turchi, Janita N.; Duyn, Jeff H.

2016-01-01

Changes in brain activity accompanying shifts in vigilance and arousal can interfere with the study of other intrinsic and task-evoked characteristics of brain function. However, the difficulty of tracking and modeling the arousal state during functional MRI (fMRI) typically precludes the assessment of arousal-dependent influences on fMRI signals. Here we combine fMRI, electrophysiology, and the monitoring of eyelid behavior to demonstrate an approach for tracking continuous variations in arousal level from fMRI data. We first characterize the spatial distribution of fMRI signal fluctuations that track a measure of behavioral arousal; taking this pattern as a template, and using the local field potential as a simultaneous and independent measure of cortical activity, we observe that the time-varying expression level of this template in fMRI data provides a close approximation of electrophysiological arousal. We discuss the potential benefit of these findings for increasing the sensitivity of fMRI as a cognitive and clinical biomarker. PMID:27051064

A functional neuroimaging review of obesity, appetitive hormones and ingestive behavior.

PubMed

Burger, Kyle S; Berner, Laura A

2014-09-01

Adequate energy intake is vital for the survival of humans and is regulated by complex homeostatic and hedonic mechanisms. Supported by functional MRI (fMRI) studies that consistently demonstrate differences in brain response as a function of weight status during exposure to appetizing food stimuli, it has been posited that hedonically driven food intake contributes to weight gain and obesity maintenance. These food reward theories of obesity are reliant on the notion that the aberrant brain response to food stimuli relates directly to ingestive behavior, specifically, excess food intake. Importantly, functioning of homeostatic neuroendocrine regulators of food intake, such as leptin and ghrelin, are impacted by weight status. Thus, data from studies that evaluate the effect on weight status on brain response to food may be a result of differences in neuroendocrine functioning and/or behavior. In the present review, we examine the influence of weight and weight change, exogenous administration of appetitive hormones, and ingestive behavior on BOLD response to food stimuli. Published by Elsevier Inc.

Correlated gene expression and anatomical communication support synchronized brain activity in the mouse functional connectome.

PubMed

Mills, Brian D; Grayson, David S; Shunmugavel, Anandakumar; Miranda-Dominguez, Oscar; Feczko, Eric; Earl, Eric; Neve, Kim; Fair, Damien A

2018-05-22

Cognition and behavior depend on synchronized intrinsic brain activity that is organized into functional networks across the brain. Research has investigated how anatomical connectivity both shapes and is shaped by these networks, but not how anatomical connectivity interacts with intra-areal molecular properties to drive functional connectivity. Here, we present a novel linear model to explain functional connectivity by integrating systematically obtained measurements of axonal connectivity, gene expression, and resting state functional connectivity MRI in the mouse brain. The model suggests that functional connectivity arises from both anatomical links and inter-areal similarities in gene expression. By estimating these effects, we identify anatomical modules in which correlated gene expression and anatomical connectivity support functional connectivity. Along with providing evidence that not all genes equally contribute to functional connectivity, this research establishes new insights regarding the biological underpinnings of coordinated brain activity measured by BOLD fMRI. SIGNIFICANCE STATEMENT Efforts at characterizing the functional connectome with fMRI have risen exponentially over the last decade. Yet despite this rise, the biological underpinnings of these functional measurements are still largely unknown. The current report begins to fill this void by investigating the molecular underpinnings of the functional connectome through an integration of systematically obtained structural information and gene expression data throughout the rodent brain. We find that both white matter connectivity and similarity in regional gene expression relate to resting state functional connectivity. The current report furthers our understanding of the biological underpinnings of the functional connectome and provides a linear model that can be utilized to streamline preclinical animal studies of disease. Copyright © 2018 the authors.

Recording event-related activity under hostile magnetic resonance environment: Is multimodal EEG/ERP-MRI recording possible?

PubMed

Karakaş, H M; Karakaş, S; Ozkan Ceylan, A; Tali, E T

2009-08-01

Event-related potentials (ERPs) have high temporal resolution, but insufficient spatial resolution; the converse is true for the functional imaging techniques. The purpose of the study was to test the utility of a multimodal EEG/ERP-MRI technique which combines electroencephalography (EEG) and magnetic resonance imaging (MRI) for a simultaneously high temporal and spatial resolution. The sample consisted of 32 healthy young adults of both sexes. Auditory stimuli were delivered according to the active and passive oddball paradigms in the MRI environment (MRI-e) and in the standard conditions of the electrophysiology laboratory environment (Lab-e). Tasks were presented in a fixed order. Participants were exposed to the recording environments in a counterbalanced order. EEG data were preprocessed for MRI-related artifacts. Source localization was made using a current density reconstruction technique. The ERP waveforms for the MRI-e were morphologically similar to those for the Lab-e. The effect of the recording environment, experimental paradigm and electrode location were analyzed using a 2x2x3 analysis of variance for repeated measures. The ERP components in the two environments showed parametric variations and characteristic topographical distributions. The calculated sources were in line with the related literature. The findings indicated effortful cognitive processing in MRI-e. The study provided preliminary data on the feasibility of the multimodal EEG/ERP-MRI technique. It also indicated lines of research that are to be pursued for a decisive testing of this technique and its implementation to clinical practice.

Effects of Bright Light Therapy of Sleep, Cognition, Brain Function, and Neurochemistry in Mild Traumatic Brain Injury

DTIC Science & Technology

2012-01-01

computerized stimulation paradigms for use during functional neuroimaging (i.e., MSIT). Accomplishments: • The following computer tasks were...and Stability Test. • Programming of all computerized functional MRI stimulation paradigms and assessment tasks using E-prime software was completed...Computer stimulation paradigms were tested in the scanner environment to ensure that they could be presented and seen by subjects in the scanner

Correlates of figure-ground segregation in fMRI.

PubMed

Skiera, G; Petersen, D; Skalej, M; Fahle, M

2000-01-01

We investigated which correlates of figure-ground-segregation can be detected by means of functional magnetic resonance imaging (fMRI). Five subjects were scanned with a Siemens Vision 1.5 T system. Motion, colour, and luminance-defined checkerboards were presented with alternating control conditions containing one of the two features of the checkerboard. We find a segregation-specific activation in V1 for all subjects and all stimuli and conclude that neural mechanisms exist as early as in the primary visual cortex that are sensitive to figure-ground segregation.

Neural Basis of Enhanced Executive Function in Older Video Game Players: An fMRI Study.

PubMed

Wang, Ping; Zhu, Xing-Ting; Qi, Zhigang; Huang, Silin; Li, Hui-Jie

2017-01-01

Video games have been found to have positive influences on executive function in older adults; however, the underlying neural basis of the benefits from video games has been unclear. Adopting a task-based functional magnetic resonance imaging (fMRI) study targeted at the flanker task, the present study aims to explore the neural basis of the improved executive function in older adults with video game experiences. Twenty video game players (VGPs) and twenty non-video game players (NVGPs) of 60 years of age or older participated in the present study, and there are no significant differences in age ( t = 0.62, p = 0.536), gender ratio ( t = 1.29, p = 0.206) and years of education ( t = 1.92, p = 0.062) between VGPs and NVGPs. The results show that older VGPs present significantly better behavioral performance than NVGPs. Older VGPs activate greater than NVGPs in brain regions, mainly in frontal-parietal areas, including the right dorsolateral prefrontal cortex, the left supramarginal gyrus, the right angular gyrus, the right precuneus and the left paracentral lobule. The present study reveals that video game experiences may have positive influences on older adults in behavioral performance and the underlying brain activation. These results imply the potential role that video games can play as an effective tool to improve cognitive ability in older adults.

Optimizing real time fMRI neurofeedback for therapeutic discovery and development

PubMed Central

Stoeckel, L.E.; Garrison, K.A.; Ghosh, S.; Wighton, P.; Hanlon, C.A.; Gilman, J.M.; Greer, S.; Turk-Browne, N.B.; deBettencourt, M.T.; Scheinost, D.; Craddock, C.; Thompson, T.; Calderon, V.; Bauer, C.C.; George, M.; Breiter, H.C.; Whitfield-Gabrieli, S.; Gabrieli, J.D.; LaConte, S.M.; Hirshberg, L.; Brewer, J.A.; Hampson, M.; Van Der Kouwe, A.; Mackey, S.; Evins, A.E.

2014-01-01

While reducing the burden of brain disorders remains a top priority of organizations like the World Health Organization and National Institutes of Health, the development of novel, safe and effective treatments for brain disorders has been slow. In this paper, we describe the state of the science for an emerging technology, real time functional magnetic resonance imaging (rtfMRI) neurofeedback, in clinical neurotherapeutics. We review the scientific potential of rtfMRI and outline research strategies to optimize the development and application of rtfMRI neurofeedback as a next generation therapeutic tool. We propose that rtfMRI can be used to address a broad range of clinical problems by improving our understanding of brain–behavior relationships in order to develop more specific and effective interventions for individuals with brain disorders. We focus on the use of rtfMRI neurofeedback as a clinical neurotherapeutic tool to drive plasticity in brain function, cognition, and behavior. Our overall goal is for rtfMRI to advance personalized assessment and intervention approaches to enhance resilience and reduce morbidity by correcting maladaptive patterns of brain function in those with brain disorders. PMID:25161891

Estimation of gas and tissue lung volumes by MRI: functional approach of lung imaging.

PubMed

Qanadli, S D; Orvoen-Frija, E; Lacombe, P; Di Paola, R; Bittoun, J; Frija, G

1999-01-01

The purpose of this work was to assess the accuracy of MRI for the determination of lung gas and tissue volumes. Fifteen healthy subjects underwent MRI of the thorax and pulmonary function tests [vital capacity (VC) and total lung capacity (TLC)] in the supine position. MR examinations were performed at inspiration and expiration. Lung volumes were measured by a previously validated technique on phantoms. Both individual and total lung volumes and capacities were calculated. MRI total vital capacity (VC(MRI)) was compared with spirometric vital capacity (VC(SP)). Capacities were correlated to lung volumes. Tissue volume (V(T)) was estimated as the difference between the total lung volume at full inspiration and the TLC. No significant difference was seen between VC(MRI) and VC(SP). Individual capacities were well correlated (r = 0.9) to static volume at full inspiration. The V(T) was estimated to be 836+/-393 ml. This preliminary study demonstrates that MRI can accurately estimate lung gas and tissue volumes. The proposed approach appears well suited for functional imaging of the lung.

Relating resting-state fMRI and EEG whole-brain connectomes across frequency bands.

PubMed

Deligianni, Fani; Centeno, Maria; Carmichael, David W; Clayden, Jonathan D

2014-01-01

Whole brain functional connectomes hold promise for understanding human brain activity across a range of cognitive, developmental and pathological states. So called resting-state (rs) functional MRI studies have contributed to the brain being considered at a macroscopic scale as a set of interacting regions. Interactions are defined as correlation-based signal measurements driven by blood oxygenation level dependent (BOLD) contrast. Understanding the neurophysiological basis of these measurements is important in conveying useful information about brain function. Local coupling between BOLD fMRI and neurophysiological measurements is relatively well defined, with evidence that gamma (range) frequency EEG signals are the closest correlate of BOLD fMRI changes during cognitive processing. However, it is less clear how whole-brain network interactions relate during rest where lower frequency signals have been suggested to play a key role. Simultaneous EEG-fMRI offers the opportunity to observe brain network dynamics with high spatio-temporal resolution. We utilize these measurements to compare the connectomes derived from rs-fMRI and EEG band limited power (BLP). Merging this multi-modal information requires the development of an appropriate statistical framework. We relate the covariance matrices of the Hilbert envelope of the source localized EEG signal across bands to the covariance matrices derived from rs-fMRI with the means of statistical prediction based on sparse Canonical Correlation Analysis (sCCA). Subsequently, we identify the most prominent connections that contribute to this relationship. We compare whole-brain functional connectomes based on their geodesic distance to reliably estimate the performance of the prediction. The performance of predicting fMRI from EEG connectomes is considerably better than predicting EEG from fMRI across all bands, whereas the connectomes derived in low frequency EEG bands resemble best rs-fMRI connectivity.

Relating resting-state fMRI and EEG whole-brain connectomes across frequency bands

PubMed Central

Deligianni, Fani; Centeno, Maria; Carmichael, David W.; Clayden, Jonathan D.

2014-01-01

Whole brain functional connectomes hold promise for understanding human brain activity across a range of cognitive, developmental and pathological states. So called resting-state (rs) functional MRI studies have contributed to the brain being considered at a macroscopic scale as a set of interacting regions. Interactions are defined as correlation-based signal measurements driven by blood oxygenation level dependent (BOLD) contrast. Understanding the neurophysiological basis of these measurements is important in conveying useful information about brain function. Local coupling between BOLD fMRI and neurophysiological measurements is relatively well defined, with evidence that gamma (range) frequency EEG signals are the closest correlate of BOLD fMRI changes during cognitive processing. However, it is less clear how whole-brain network interactions relate during rest where lower frequency signals have been suggested to play a key role. Simultaneous EEG-fMRI offers the opportunity to observe brain network dynamics with high spatio-temporal resolution. We utilize these measurements to compare the connectomes derived from rs-fMRI and EEG band limited power (BLP). Merging this multi-modal information requires the development of an appropriate statistical framework. We relate the covariance matrices of the Hilbert envelope of the source localized EEG signal across bands to the covariance matrices derived from rs-fMRI with the means of statistical prediction based on sparse Canonical Correlation Analysis (sCCA). Subsequently, we identify the most prominent connections that contribute to this relationship. We compare whole-brain functional connectomes based on their geodesic distance to reliably estimate the performance of the prediction. The performance of predicting fMRI from EEG connectomes is considerably better than predicting EEG from fMRI across all bands, whereas the connectomes derived in low frequency EEG bands resemble best rs-fMRI connectivity. PMID:25221467

Motion correction for functional MRI with three-dimensional hybrid radial-Cartesian EPI.

PubMed

Graedel, Nadine N; McNab, Jennifer A; Chiew, Mark; Miller, Karla L

2017-08-01

Subject motion is a major source of image degradation for functional MRI (fMRI), especially when using multishot sequences like three-dimensional (3D EPI). We present a hybrid radial-Cartesian 3D EPI trajectory enabling motion correction in k-space for functional MRI. The EPI "blades" of the 3D hybrid radial-Cartesian EPI sequence, called TURBINE, are rotated about the phase-encoding axis to fill out a cylinder in 3D k-space. Angular blades are acquired over time using a golden-angle rotation increment, allowing reconstruction at flexible temporal resolution. The self-navigating properties of the sequence are used to determine motion parameters from a high temporal-resolution navigator time series. The motion is corrected in k-space as part of the image reconstruction, and evaluated for experiments with both cued and natural motion. We demonstrate that the motion correction works robustly and that we can achieve substantial artifact reduction as well as improvement in temporal signal-to-noise ratio and fMRI activation in the presence of both severe and subtle motion. We show the potential for hybrid radial-Cartesian 3D EPI to substantially reduce artifacts for application in fMRI, especially for subject groups with significant head motion. The motion correction approach does not prolong the scan, and no extra hardware is required. Magn Reson Med 78:527-540, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.

Physiologic noise regression, motion regression, and TOAST dynamic field correction in complex-valued fMRI time series.

PubMed

Hahn, Andrew D; Rowe, Daniel B

2012-02-01

As more evidence is presented suggesting that the phase, as well as the magnitude, of functional MRI (fMRI) time series may contain important information and that there are theoretical drawbacks to modeling functional response in the magnitude alone, removing noise in the phase is becoming more important. Previous studies have shown that retrospective correction of noise from physiologic sources can remove significant phase variance and that dynamic main magnetic field correction and regression of estimated motion parameters also remove significant phase fluctuations. In this work, we investigate the performance of physiologic noise regression in a framework along with correction for dynamic main field fluctuations and motion regression. Our findings suggest that including physiologic regressors provides some benefit in terms of reduction in phase noise power, but it is small compared to the benefit of dynamic field corrections and use of estimated motion parameters as nuisance regressors. Additionally, we show that the use of all three techniques reduces phase variance substantially, removes undesirable spatial phase correlations and improves detection of the functional response in magnitude and phase. Copyright © 2011 Elsevier Inc. All rights reserved.

Control of nucleus accumbens activity with neurofeedback

PubMed Central

Greer, Stephanie M.; Trujillo, Andrew J.; Glover, Gary H.; Knutson, Brian

2014-01-01

The nucleus accumbens (NAcc) plays critical roles in healthy motivation and learning, as well as in psychiatric disorders (including schizophrenia and attention deficit hyperactivity disorder). Thus, techniques that confer control of NAcc activity might inspire new therapeutic interventions. By providing second-to-second temporal resolution of activity in small subcortical regions, functional magnetic resonance imaging (fMRI) can resolve online changes in NAcc activity, which can then be presented as “neurofeedback.” In an fMRI-based neurofeedback experiment designed to elicit NAcc activity, we found that subjects could increase their own NAcc activity, and that display of neurofeedback significantly enhanced their ability to do so. Subjects were not as capable of decreasing their NAcc activity, however, and enhanced control did not persist after subsequent removal of neurofeedback. Further analyses suggested that individuals who recruited positive arousal affect were better able to increase NAcc activity in response to neurofeedback, and that NAcc neurofeedback also elicited functionally correlated activity in the medial prefrontal cortex. Together, these findings suggest that humans can modulate their own NAcc activity and that fMRI-based neurofeedback may augment their efforts. The observed association between positive arousal and effective NAcc control further supports an anticipatory affect account of NAcc function. PMID:24705203

Functional-anatomic study of episodic retrieval using fMRI. I. Retrieval effort versus retrieval success.

PubMed

Buckner, R L; Koutstaal, W; Schacter, D L; Wagner, A D; Rosen, B R

1998-04-01

A number of recent functional imaging studies have identified brain areas activated during tasks involving episodic memory retrieval. The identification of such areas provides a foundation for targeted hypotheses regarding the more specific contributions that these areas make to episodic retrieval. As a beginning effort toward such an endeavor, whole-brain functional magnetic resonance imaging (fMRI) was used to examine 14 subjects during episodic word recognition in a block-designed fMRI experiment. Study conditions were manipulated by presenting either shallow or deep encoding tasks. This manipulation yielded two recognition conditions that differed with regard to retrieval effort and retrieval success: shallow encoding yielded low levels of recognition success with high levels of retrieval effort, and deep encoding yielded high levels of recognition success with low levels of effort. Many brain areas were activated in common by these two recognition conditions compared to a low-level fixation condition, including left and right prefrontal regions often detected during PET episodic retrieval paradigms (e.g., R. L. Buckner et al., 1996, J. Neurosci. 16, 6219-6235) thereby generalizing these findings to fMRI. Characterization of the activated regions in relation to the separate recognition conditions showed (1) bilateral anterior insular regions and a left dorsal prefrontal region were more active after shallow encoding, when retrieval demanded greatest effort, and (2) right anterior prefrontal cortex, which has been implicated in episodic retrieval, was most active during successful retrieval after deep encoding. We discuss these findings in relation to component processes involved in episodic retrieval and in the context of a companion study using event-related fMRI.

A Systematic Review and Meta-analysis of Neuroimaging in Oppositional Defiant Disorder (ODD) and Conduct Disorder (CD) Taking Attention-Deficit Hyperactivity Disorder (ADHD) Into Account.

PubMed

Noordermeer, Siri D S; Luman, Marjolein; Oosterlaan, Jaap

2016-03-01

Oppositional defiant disorder (ODD) and conduct disorder (CD) are common behavioural disorders in childhood and adolescence and are associated with brain abnormalities. This systematic review and meta-analysis investigates structural (sMRI) and functional MRI (fMRI) findings in individuals with ODD/CD with and without attention-deficit hyperactivity disorder (ADHD). Online databases were searched for controlled studies, resulting in 12 sMRI and 17 fMRI studies. In line with current models on ODD/CD, studies were classified in hot and cool executive functioning (EF). Both the meta-analytic and narrative reviews showed evidence of smaller brain structures and lower brain activity in individuals with ODD/CD in mainly hot EF-related areas: bilateral amygdala, bilateral insula, right striatum, left medial/superior frontal gyrus, and left precuneus. Evidence was present in both structural and functional studies, and irrespective of the presence of ADHD comorbidity. There is strong evidence that abnormalities in the amygdala are specific for ODD/CD as compared to ADHD, and correlational studies further support the association between abnormalities in the amygdala and ODD/CD symptoms. Besides the left precuneus, there was no evidence for abnormalities in typical cool EF related structures, such as the cerebellum and dorsolateral prefrontal cortex. Resulting areas are associated with emotion-processing, error-monitoring, problem-solving and self-control; areas associated with neurocognitive and behavioural deficits implicated in ODD/CD. Our findings confirm the involvement of hot, and to a smaller extent cool, EF associated brain areas in ODD/CD, and support an integrated model for ODD/CD (e.g. Blair, Development and Psychopathology, 17(3), 865-891, 2005).

Incidental Memory Encoding Assessed with Signal Detection Theory and Functional Magnetic Resonance Imaging (fMRI).

PubMed

Clemens, Benjamin; Regenbogen, Christina; Koch, Kathrin; Backes, Volker; Romanczuk-Seiferth, Nina; Pauly, Katharina; Shah, N Jon; Schneider, Frank; Habel, Ute; Kellermann, Thilo

2015-01-01

In functional magnetic resonance imaging (fMRI) studies that apply a "subsequent memory" approach, successful encoding is indicated by increased fMRI activity during the encoding phase for hits vs. misses, in areas underlying memory encoding such as the hippocampal formation. Signal-detection theory (SDT) can be used to analyze memory-related fMRI activity as a function of the participant's memory trace strength (d(')). The goal of the present study was to use SDT to examine the relationship between fMRI activity during incidental encoding and participants' recognition performance. To implement a new approach, post-experimental group assignment into High- or Low Performers (HP or LP) was based on 29 healthy participants' recognition performance, assessed with SDT. The analyses focused on the interaction between the factors group (HP vs. LP) and recognition performance (hits vs. misses). A whole-brain analysis revealed increased activation for HP vs. LP during incidental encoding for remembered vs. forgotten items (hits > misses) in the insula/temporo-parietal junction (TPJ) and the fusiform gyrus (FFG). Parameter estimates in these regions exhibited a significant positive correlation with d('). As these brain regions are highly relevant for salience detection (insula), stimulus-driven attention (TPJ), and content-specific processing of mnemonic stimuli (FFG), we suggest that HPs' elevated memory performance was associated with enhanced attentional and content-specific sensory processing during the encoding phase. We provide first correlative evidence that encoding-related activity in content-specific sensory areas and content-independent attention and salience detection areas influences memory performance in a task with incidental encoding of facial stimuli. Based on our findings, we discuss whether the aforementioned group differences in brain activity during incidental encoding might constitute the basis of general differences in memory performance between HP and LP.

Impact of functional MRI data preprocessing pipeline on default-mode network detectability in patients with disorders of consciousness.

PubMed

Andronache, Adrian; Rosazza, Cristina; Sattin, Davide; Leonardi, Matilde; D'Incerti, Ludovico; Minati, Ludovico

2013-01-01

An emerging application of resting-state functional MRI (rs-fMRI) is the study of patients with disorders of consciousness (DoC), where integrity of default-mode network (DMN) activity is associated to the clinical level of preservation of consciousness. Due to the inherent inability to follow verbal instructions, arousal induced by scanning noise and postural pain, these patients tend to exhibit substantial levels of movement. This results in spurious, non-neural fluctuations of the rs-fMRI signal, which impair the evaluation of residual functional connectivity. Here, the effect of data preprocessing choices on the detectability of the DMN was systematically evaluated in a representative cohort of 30 clinically and etiologically heterogeneous DoC patients and 33 healthy controls. Starting from a standard preprocessing pipeline, additional steps were gradually inserted, namely band-pass filtering (BPF), removal of co-variance with the movement vectors, removal of co-variance with the global brain parenchyma signal, rejection of realignment outlier volumes and ventricle masking. Both independent-component analysis (ICA) and seed-based analysis (SBA) were performed, and DMN detectability was assessed quantitatively as well as visually. The results of the present study strongly show that the detection of DMN activity in the sub-optimal fMRI series acquired on DoC patients is contingent on the use of adequate filtering steps. ICA and SBA are differently affected but give convergent findings for high-grade preprocessing. We propose that future studies in this area should adopt the described preprocessing procedures as a minimum standard to reduce the probability of wrongly inferring that DMN activity is absent.

MRI tools for assessment of microstructure and nephron function of the kidney.

PubMed

Xie, Luke; Bennett, Kevin M; Liu, Chunlei; Johnson, G Allan; Zhang, Jeff Lei; Lee, Vivian S

2016-12-01

MRI can provide excellent detail of renal structure and function. Recently, novel MR contrast mechanisms and imaging tools have been developed to evaluate microscopic kidney structures including the tubules and glomeruli. Quantitative MRI can assess local tubular function and is able to determine the concentrating mechanism of the kidney noninvasively in real time. Measuring single nephron function is now a near possibility. In parallel to advancing imaging techniques for kidney microstructure is a need to carefully understand the relationship between the local source of MRI contrast and the underlying physiological change. The development of these imaging markers can impact the accurate diagnosis and treatment of kidney disease. This study reviews the novel tools to examine kidney microstructure and local function and demonstrates the application of these methods in renal pathophysiology. Copyright © 2016 the American Physiological Society.

Scale-Free and Multifractal Time Dynamics of fMRI Signals during Rest and Task

PubMed Central

Ciuciu, P.; Varoquaux, G.; Abry, P.; Sadaghiani, S.; Kleinschmidt, A.

2012-01-01

Scaling temporal dynamics in functional MRI (fMRI) signals have been evidenced for a decade as intrinsic characteristics of ongoing brain activity (Zarahn et al., 1997). Recently, scaling properties were shown to fluctuate across brain networks and to be modulated between rest and task (He, 2011): notably, Hurst exponent, quantifying long memory, decreases under task in activating and deactivating brain regions. In most cases, such results were obtained: First, from univariate (voxelwise or regionwise) analysis, hence focusing on specific cognitive systems such as Resting-State Networks (RSNs) and raising the issue of the specificity of this scale-free dynamics modulation in RSNs. Second, using analysis tools designed to measure a single scaling exponent related to the second order statistics of the data, thus relying on models that either implicitly or explicitly assume Gaussianity and (asymptotic) self-similarity, while fMRI signals may significantly depart from those either of those two assumptions (Ciuciu et al., 2008; Wink et al., 2008). To address these issues, the present contribution elaborates on the analysis of the scaling properties of fMRI temporal dynamics by proposing two significant variations. First, scaling properties are technically investigated using the recently introduced Wavelet Leader-based Multifractal formalism (WLMF; Wendt et al., 2007). This measures a collection of scaling exponents, thus enables a richer and more versatile description of scale invariance (beyond correlation and Gaussianity), referred to as multifractality. Also, it benefits from improved estimation performance compared to tools previously used in the literature. Second, scaling properties are investigated in both RSN and non-RSN structures (e.g., artifacts), at a broader spatial scale than the voxel one, using a multivariate approach, namely the Multi-Subject Dictionary Learning (MSDL) algorithm (Varoquaux et al., 2011) that produces a set of spatial components that appear more sparse than their Independent Component Analysis (ICA) counterpart. These tools are combined and applied to a fMRI dataset comprising 12 subjects with resting-state and activation runs (Sadaghiani et al., 2009). Results stemming from those analysis confirm the already reported task-related decrease of long memory in functional networks, but also show that it occurs in artifacts, thus making this feature not specific to functional networks. Further, results indicate that most fMRI signals appear multifractal at rest except in non-cortical regions. Task-related modulation of multifractality appears only significant in functional networks and thus can be considered as the key property disentangling functional networks from artifacts. These finding are discussed in the light of the recent literature reporting scaling dynamics of EEG microstate sequences at rest and addressing non-stationarity issues in temporally independent fMRI modes. PMID:22715328

Advanced magnetic resonance imaging of neurodegenerative diseases.

PubMed

Agosta, Federica; Galantucci, Sebastiano; Filippi, Massimo

2017-01-01

Magnetic resonance imaging (MRI) is playing an increasingly important role in the study of neurodegenerative diseases, delineating the structural and functional alterations determined by these conditions. Advanced MRI techniques are of special interest for their potential to characterize the signature of each neurodegenerative condition and aid both the diagnostic process and the monitoring of disease progression. This aspect will become crucial when disease-modifying (personalized) therapies will be established. MRI techniques are very diverse and go from the visual inspection of MRI scans to more complex approaches, such as manual and automatic volume measurements, diffusion tensor MRI, and functional MRI. All these techniques allow us to investigate the different features of neurodegeneration. In this review, we summarize the most recent advances concerning the use of MRI in some of the most important neurodegenerative conditions, putting an emphasis on the advanced techniques.

TWave: High-Order Analysis of Functional MRI

PubMed Central

Barnathan, Michael; Megalooikonomou, Vasileios; Faloutsos, Christos; Faro, Scott; Mohamed, Feroze B.

2011-01-01

The traditional approach to functional image analysis models images as matrices of raw voxel intensity values. Although such a representation is widely utilized and heavily entrenched both within neuroimaging and in the wider data mining community, the strong interactions among space, time, and categorical modes such as subject and experimental task inherent in functional imaging yield a dataset with “high-order” structure, which matrix models are incapable of exploiting. Reasoning across all of these modes of data concurrently requires a high-order model capable of representing relationships between all modes of the data in tandem. We thus propose to model functional MRI data using tensors, which are high-order generalizations of matrices equivalent to multidimensional arrays or data cubes. However, several unique challenges exist in the high-order analysis of functional medical data: naïve tensor models are incapable of exploiting spatiotemporal locality patterns, standard tensor analysis techniques exhibit poor efficiency, and mixtures of numeric and categorical modes of data are very often present in neuroimaging experiments. Formulating the problem of image clustering as a form of Latent Semantic Analysis and using the WaveCluster algorithm as a baseline, we propose a comprehensive hybrid tensor and wavelet framework for clustering, concept discovery, and compression of functional medical images which successfully addresses these challenges. Our approach reduced runtime and dataset size on a 9.3 GB finger opposition motor task fMRI dataset by up to 98% while exhibiting improved spatiotemporal coherence relative to standard tensor, wavelet, and voxel-based approaches. Our clustering technique was capable of automatically differentiating between the frontal areas of the brain responsible for task-related habituation and the motor regions responsible for executing the motor task, in contrast to a widely used fMRI analysis program, SPM, which only detected the latter region. Furthermore, our approach discovered latent concepts suggestive of subject handedness nearly 100x faster than standard approaches. These results suggest that a high-order model is an integral component to accurate scalable functional neuroimaging. PMID:21729758

Hypercapnic evaluation of vascular reactivity in healthy aging and acute stroke via functional MRI.

PubMed

Raut, Ryan V; Nair, Veena A; Sattin, Justin A; Prabhakaran, Vivek

2016-01-01

Functional MRI (fMRI) is well-established for the study of brain function in healthy populations, although its clinical application has proven more challenging. Specifically, cerebrovascular reactivity (CVR), which allows the assessment of the vascular response that serves as the basis for fMRI, has been shown to be reduced in healthy aging as well as in a range of diseases, including chronic stroke. However, the timing of when this occurs relative to the stroke event is unclear. We used a breath-hold fMRI task to evaluate CVR across gray matter in a group of acute stroke patients (< 10 days from stroke; N = 22) to address this question. These estimates were compared with those from both age-matched (N = 22) and younger (N = 22) healthy controls. As expected, young controls had the greatest mean CVR, as indicated by magnitude and extent of fMRI activation; however, stroke patients did not differ from age-matched controls. Moreover, the ipsilesional and contralesional hemispheres of stroke patients did not differ with respect to any of these measures. These findings suggest that fMRI remains a valid tool within the first few days of a stroke, particularly for group fMRI studies in which findings are compared with healthy subjects of similar age. However, given the relatively high variability in CVR observed in our stroke sample, caution is warranted when interpreting fMRI data from individual patients or a small cohort. We conclude that a breath-hold task can be a useful addition to functional imaging protocols for stroke patients.

Biology and therapy of fibromyalgia. Functional magnetic resonance imaging findings in fibromyalgia

PubMed Central

Williams, David A; Gracely, Richard H

2006-01-01

Techniques in neuroimaging such as functional magnetic resonance imaging (fMRI) have helped to provide insights into the role of supraspinal mechanisms in pain perception. This review focuses on studies that have applied fMRI in an attempt to gain a better understanding of the mechanisms involved in the processing of pain associated with fibromyalgia. This article provides an overview of the nociceptive system as it functions normally, reviews functional brain imaging methods, and integrates the existing literature utilizing fMRI to study central pain mechanisms in fibromyalgia. PMID:17254318

Control networks and hubs.

PubMed

Gratton, Caterina; Sun, Haoxin; Petersen, Steven E

2018-03-01

Executive control functions are associated with frontal, parietal, cingulate, and insular brain regions that interact through distributed large-scale networks. Here, we discuss how fMRI functional connectivity can shed light on the organization of control networks and how they interact with other parts of the brain. In the first section of our review, we present convergent evidence from fMRI functional connectivity, activation, and lesion studies that there are multiple dissociable control networks in the brain with distinct functional properties. In the second section, we discuss how graph theoretical concepts can help illuminate the mechanisms by which control networks interact with other brain regions to carry out goal-directed functions, focusing on the role of specialized hub regions for mediating cross-network interactions. Again, we use a combination of functional connectivity, lesion, and task activation studies to bolster this claim. We conclude that a large-scale network perspective provides important neurobiological constraints on the neural underpinnings of executive control, which will guide future basic and translational research into executive function and its disruption in disease. © 2017 Society for Psychophysiological Research.

Evidence for Functional Networks within the Human Brain's White Matter.

PubMed

Peer, Michael; Nitzan, Mor; Bick, Atira S; Levin, Netta; Arzy, Shahar

2017-07-05

Investigation of the functional macro-scale organization of the human cortex is fundamental in modern neuroscience. Although numerous studies have identified networks of interacting functional modules in the gray-matter, limited research was directed to the functional organization of the white-matter. Recent studies have demonstrated that the white-matter exhibits blood oxygen level-dependent signal fluctuations similar to those of the gray-matter. Here we used these signal fluctuations to investigate whether the white-matter is organized as functional networks by applying a clustering analysis on resting-state functional MRI (RSfMRI) data from white-matter voxels, in 176 subjects (of both sexes). This analysis indicated the existence of 12 symmetrical white-matter functional networks, corresponding to combinations of white-matter tracts identified by diffusion tensor imaging. Six of the networks included interhemispheric commissural bridges traversing the corpus callosum. Signals in white-matter networks correlated with signals from functional gray-matter networks, providing missing knowledge on how these distributed networks communicate across large distances. These findings were replicated in an independent subject group and were corroborated by seed-based analysis in small groups and individual subjects. The identified white-matter functional atlases and analysis codes are available at http://mind.huji.ac.il/white-matter.aspx Our results demonstrate that the white-matter manifests an intrinsic functional organization as interacting networks of functional modules, similarly to the gray-matter, which can be investigated using RSfMRI. The discovery of functional networks within the white-matter may open new avenues of research in cognitive neuroscience and clinical neuropsychiatry. SIGNIFICANCE STATEMENT In recent years, functional MRI (fMRI) has revolutionized all fields of neuroscience, enabling identifications of functional modules and networks in the human brain. However, most fMRI studies ignored a major part of the brain, the white-matter, discarding signals from it as arising from noise. Here we use resting-state fMRI data from 176 subjects to show that signals from the human white-matter contain meaningful information. We identify 12 functional networks composed of interacting long-distance white-matter tracts. Moreover, we show that these networks are highly correlated to resting-state gray-matter networks, highlighting their functional role. Our findings enable reinterpretation of many existing fMRI datasets, and suggest a new way to explore the white-matter role in cognition and its disturbances in neuropsychiatric disorders. Copyright © 2017 the authors 0270-6474/17/376394-14$15.00/0.

Anatomo-clinical overlapping maps (AnaCOM): a new method to create anatomo-functional maps from neuropsychological tests and structural MRI scan of subjects with brain lesions

NASA Astrophysics Data System (ADS)

Kinkingnehun, Serge R. J.; du Boisgueheneuc, Foucaud; Golmard, Jean-Louis; Zhang, Sandy X.; Levy, Richard; Dubois, Bruno

2004-04-01

We have developed a new technique to analyze correlations between brain anatomy and its neurological functions. The technique is based on the anatomic MRI of patients with brain lesions who are administered neuropsychological tests. Brain lesions of the MRI scans are first manually segmented. The MRI volumes are then normalized to a reference map, using the segmented area as a mask. After normalization, the brain lesions of the MRI are segmented again in order to redefine the border of the lesions in the context of the normalized brain. Once the MRI is segmented, the patient's score on the neuropsychological test is assigned to each voxel in the lesioned area, while the rest of the voxels of the image are set to 0. Subsequently, the individual patient's MRI images are superimposed, and each voxel is reassigned the average score of the patients who have a lesion at that voxel. A threshold is applied to remove regions having less than three overlaps. This process leads to an anatomo-functional map that links brain areas to functional loss. Other maps can be created to aid in analyzing the functional maps, such as one that indicates the 95% confidence interval of the averaged scores for each area. This anatomo-clinical overlapping map (AnaCOM) method was used to obtain functional maps from patients with lesions in the superior frontal gyrus. By finding particular subregions more responsible for a particular deficit, this method can generate new hypotheses to be tested by conventional group methods.

Protein corona affects the relaxivity and MRI contrast efficiency of magnetic nanoparticles

NASA Astrophysics Data System (ADS)

Amiri, Houshang; Bordonali, Lorenzo; Lascialfari, Alessandro; Wan, Sha; Monopoli, Marco P.; Lynch, Iseult; Laurent, Sophie; Mahmoudi, Morteza

2013-08-01

Magnetic nanoparticles (NPs) are increasingly being considered for use in biomedical applications such as biosensors, imaging contrast agents and drug delivery vehicles. In a biological fluid, proteins associate in a preferential manner with NPs. The small sizes and high curvature angles of NPs influence the types and amounts of proteins present on their surfaces. This differential display of proteins bound to the surface of NPs can influence the tissue distribution, cellular uptake and biological effects of NPs. To date, the effects of adsorption of a protein corona (PC) on the magnetic properties of NPs have not been considered, despite the fact that some of their potential applications require their use in human blood. Here, to investigate the effects of a PC (using fetal bovine serum) on the MRI contrast efficiency of superparamagnetic iron oxide NPs (SPIONs), we have synthesized two series of SPIONs with variation in the thickness and functional groups (i.e. surface charges) of the dextran surface coating. We have observed that different physico-chemical characteristics of the dextran coatings on the SPIONs lead to the formation of PCs of different compositions. 1H relaxometry was used to obtain the longitudinal, r1, and transverse, r2, relaxivities of the SPIONs without and with a PC, as a function of the Larmor frequency. The transverse relaxivity, which determines the efficiency of negative contrast agents (CAs), is very much dependent on the functional group and the surface charge of the SPIONs' coating. The presence of the PC did not alter the relaxivity of plain SPIONs, while it slightly increased the relaxivity of the negatively charged SPIONs and dramatically decreased the relaxivity of the positively charged ones, which was coupled with particle agglomeration in the presence of the proteins. To confirm the effect of the PC on the MRI contrast efficiency, in vitro MRI experiments at ν = 8.5 MHz were performed using a low-field MRI scanner. The MRI contrasts, produced by different samples, were fully in agreement with the relaxometry findings.Magnetic nanoparticles (NPs) are increasingly being considered for use in biomedical applications such as biosensors, imaging contrast agents and drug delivery vehicles. In a biological fluid, proteins associate in a preferential manner with NPs. The small sizes and high curvature angles of NPs influence the types and amounts of proteins present on their surfaces. This differential display of proteins bound to the surface of NPs can influence the tissue distribution, cellular uptake and biological effects of NPs. To date, the effects of adsorption of a protein corona (PC) on the magnetic properties of NPs have not been considered, despite the fact that some of their potential applications require their use in human blood. Here, to investigate the effects of a PC (using fetal bovine serum) on the MRI contrast efficiency of superparamagnetic iron oxide NPs (SPIONs), we have synthesized two series of SPIONs with variation in the thickness and functional groups (i.e. surface charges) of the dextran surface coating. We have observed that different physico-chemical characteristics of the dextran coatings on the SPIONs lead to the formation of PCs of different compositions. 1H relaxometry was used to obtain the longitudinal, r1, and transverse, r2, relaxivities of the SPIONs without and with a PC, as a function of the Larmor frequency. The transverse relaxivity, which determines the efficiency of negative contrast agents (CAs), is very much dependent on the functional group and the surface charge of the SPIONs' coating. The presence of the PC did not alter the relaxivity of plain SPIONs, while it slightly increased the relaxivity of the negatively charged SPIONs and dramatically decreased the relaxivity of the positively charged ones, which was coupled with particle agglomeration in the presence of the proteins. To confirm the effect of the PC on the MRI contrast efficiency, in vitro MRI experiments at ν = 8.5 MHz were performed using a low-field MRI scanner. The MRI contrasts, produced by different samples, were fully in agreement with the relaxometry findings. Electronic supplementary information (ESI) available. See DOI: 10.1039/c3nr00345k

Neural Markers and Rehabilitation of Executive Functioning in Veterans with TBI and PTSD

DTIC Science & Technology

2015-10-01

with reduced irritability/impulsivity and improved social/occupational functioning. Functional magnetic resonance imaging ( fMRI ) will be used to...transport Veterans five minutes away to the Dr. Belger’s lab at UNC Hospital where EEG and fMRI will be conducted and then transport Veterans back to... fMRI was arranged through the UNC-Chapel Hill School of Medicine at month 9. Participants may either take a shuttle from the research laboratory to

Timed function tests, motor function measure, and quantitative thigh muscle MRI in ambulant children with Duchenne muscular dystrophy: A cross-sectional analysis.

PubMed

Schmidt, Simone; Hafner, Patricia; Klein, Andrea; Rubino-Nacht, Daniela; Gocheva, Vanya; Schroeder, Jonas; Naduvilekoot Devasia, Arjith; Zuesli, Stephanie; Bernert, Guenther; Laugel, Vincent; Bloetzer, Clemens; Steinlin, Maja; Capone, Andrea; Gloor, Monika; Tobler, Patrick; Haas, Tanja; Bieri, Oliver; Zumbrunn, Thomas; Fischer, Dirk; Bonati, Ulrike

2018-01-01

The development of new therapeutic agents for the treatment of Duchenne muscular dystrophy has put a focus on defining outcome measures most sensitive to capture treatment effects. This cross-sectional analysis investigates the relation between validated clinical assessments such as the 6-minute walk test, motor function measure and quantitative muscle MRI of thigh muscles in ambulant Duchenne muscular dystrophy patients, aged 6.5 to 10.8 years (mean 8.2, SD 1.1). Quantitative muscle MRI included the mean fat fraction using a 2-point Dixon technique, and transverse relaxation time (T2) measurements. All clinical assessments were highly significantly inter-correlated with p < 0.001. The strongest correlation with the motor function measure and its D1-subscore was shown by the 6-minute walk test. Clinical assessments showed no correlation with age. Importantly, quantitative muscle MRI values significantly correlated with all clinical assessments with the extensors showing the strongest correlation. In contrast to the clinical assessments, quantitative muscle MRI values were highly significantly correlated with age. In conclusion, the motor function measure and timed function tests measure disease severity in a highly comparable fashion and all tests correlated with quantitative muscle MRI values quantifying fatty muscle degeneration. Copyright © 2017 Elsevier B.V. All rights reserved.

Comparative Evaluation of Flow Quantification across the Atrioventricular Valve in Patients with Functional Univentricular Heart after Fontan's Surgery and Healthy Controls: Measurement by 4D Flow Magnetic Resonance Imaging and Streamline Visualization.

PubMed

She, Hoi Lam; Roest, Arno A W; Calkoen, Emmeline E; van den Boogaard, Pieter J; van der Geest, Rob J; Hazekamp, Mark G; de Roos, Albert; Westenberg, Jos J M

2017-01-01

To evaluate the inflow pattern and flow quantification in patients with functional univentricular heart after Fontan's operation using 4D flow magnetic resonance imaging (MRI) with streamline visualization when compared with the conventional 2D flow approach. Seven patients with functional univentricular heart after Fontan's operation and twenty-three healthy controls underwent 4D flow MRI. In two orthogonal two-chamber planes, streamline visualization was applied, and inflow angles with peak inflow velocity (PIV) were measured. Transatrioventricular flow quantification was assessed using conventional 2D multiplanar reformation (MPR) and 4D MPR tracking the annulus and perpendicular to the streamline inflow at PIV, and they were validated with net forward aortic flow. Inflow angles at PIV in the patient group demonstrated wide variation of angles and directions when compared with the control group (P < .01). The use of 4D flow MRI with streamlines visualization in quantification of the transatrioventricular flow had smaller limits of agreement (2.2 ± 4.1 mL; 95% limit of agreement -5.9-10.3 mL) when compared with the static plane assessment from 2DFlow MRI (-2.2 ± 18.5 mL; 95% limit of agreement agreement -38.5-34.1 mL). Stronger correlation was present in the 4D flow between the aortic and trans-atrioventricular flow (R 2 correlation in 4D flow: 0.893; in 2D flow: 0.786). Streamline visualization in 4D flow MRI confirmed variable atrioventricular inflow directions in patients with functional univentricular heart with previous Fontan's procedure. 4D flow aided generation of measurement planes according to the blood flood dynamics and has proven to be more accurate than the fixed plane 2D flow measurements when calculating flow quantifications. © 2016 Wiley Periodicals, Inc.

Multiple sclerosis lesions affect intrinsic functional connectivity of the spinal cord.

PubMed

Conrad, Benjamin N; Barry, Robert L; Rogers, Baxter P; Maki, Satoshi; Mishra, Arabinda; Thukral, Saakshi; Sriram, Subramaniam; Bhatia, Aashim; Pawate, Siddharama; Gore, John C; Smith, Seth A

2018-06-01

Patients with multiple sclerosis present with focal lesions throughout the spinal cord. There is a clinical need for non-invasive measurements of spinal cord activity and functional organization in multiple sclerosis, given the cord's critical role in the disease. Recent reports of spontaneous blood oxygenation level-dependent fluctuations in the spinal cord using functional MRI suggest that, like the brain, cord activity at rest is organized into distinct, synchronized functional networks among grey matter regions, likely related to motor and sensory systems. Previous studies looking at stimulus-evoked activity in the spinal cord of patients with multiple sclerosis have demonstrated increased levels of activation as well as a more bilateral distribution of activity compared to controls. Functional connectivity studies of brain networks in multiple sclerosis have revealed widespread alterations, which may take on a dynamic trajectory over the course of the disease, with compensatory increases in connectivity followed by decreases associated with structural damage. We build upon this literature by examining functional connectivity in the spinal cord of patients with multiple sclerosis. Using ultra-high field 7 T imaging along with processing strategies for robust spinal cord functional MRI and lesion identification, the present study assessed functional connectivity within cervical cord grey matter of patients with relapsing-remitting multiple sclerosis (n = 22) compared to a large sample of healthy controls (n = 56). Patient anatomical images were rated for lesions by three independent raters, with consensus ratings revealing 19 of 22 patients presented with lesions somewhere in the imaged volume. Linear mixed models were used to assess effects of lesion location on functional connectivity. Analysis in control subjects demonstrated a robust pattern of connectivity among ventral grey matter regions as well as a distinct network among dorsal regions. A gender effect was also observed in controls whereby females demonstrated higher ventral network connectivity. Wilcoxon rank-sum tests detected no differences in average connectivity or power of low frequency fluctuations in patients compared to controls. The presence of lesions was, however, associated with local alterations in connectivity with differential effects depending on columnar location. The patient results suggest that spinal cord functional networks are generally intact in relapsing-remitting multiple sclerosis but that lesions are associated with focal abnormalities in intrinsic connectivity. These findings are discussed in light of the current literature on spinal cord functional MRI and the potential neurological underpinnings.

Repeated exposure of the developing rat brain to magnetic resonance imaging did not affect neurogenesis, cell death or memory function

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

Zhu, Changlian; Department of Pediatrics, The Third Affiliated Hospital, Zhengzhou University; Gao, Jianfeng

2011-01-07

Research highlights: {yields} The effect of MRI on the developing brain is a matter of debate. {yields} Repeated exposure to MRI did not affect neurogenesis. {yields} Memory function was not affected by repeated MRI during development. {yields} Neither late gestation nor young postnatal brains were affected by MRI. {yields} Repeated MRI did not cause cell death in the neurogenic region of the hippocampus. -- Abstract: The effect of magnetic fields on the brain is a matter of debate. The objective of this study was to investigate whether repeated exposure to strong magnetic fields, such as during magnetic resonance imaging (MRI),more » could elicit changes in the developing rat brain. Embryonic day 15 (E15) and postnatal day 14 (P14) rats were exposed to MRI using a 7.05 T MR system. The animals were anesthetized and exposed for 35 min per day for 4 successive days. Control animals were anesthetized but no MRI was performed. Body temperature was maintained at 37 {sup o}C. BrdU was injected after each session (50 mg/kg). One month later, cell proliferation, neurogenesis and astrogenesis in the dentate gyrus were evaluated, revealing no effects of MRI, neither in the E15, nor in the P14 group. DNA damage in the dentate gyrus in the P14 group was evaluated on P18, 1 day after the last session, using TUNEL staining. There was no difference in the number of TUNEL-positive cells after MRI compared with controls, neither in mature neurons, nor in newborn progenitors (BrdU/TUNEL double-labeled cells). Novel object recognition was performed to assess memory function 1 month after MRI. There was no difference in the recognition index observed after MRI compared with the control rats, neither for the E15, nor for the P14 group. In conclusion, repeated exposure to MRI did not appear to affect neurogenesis, cell death or memory function in rats, neither in late gestation (E15-E18) nor in young postnatal (P14-P17) rats.« less

A Combined fMRI and DTI Examination of Functional Language Lateralization and Arcuate Fasciculus Structure: Effects of Degree versus Direction of Hand Preference

ERIC Educational Resources Information Center

Propper, Ruthe E.; O'Donnell, Lauren J.; Whalen, Stephen; Tie, Yanmei; Norton, Isaiah H.; Suarez, Ralph O.; Zollei, Lilla; Radmanesh, Alireza; Golby, Alexandra J.

2010-01-01

The present study examined the relationship between hand preference degree and direction, functional language lateralization in Broca's and Wernicke's areas, and structural measures of the arcuate fasciculus. Results revealed an effect of degree of hand preference on arcuate fasciculus structure, such that consistently-handed individuals,…

Eyes on MEGDEL: distinctive basal ganglia involvement in dystonia deafness syndrome.

PubMed

Wortmann, Saskia B; van Hasselt, Peter M; Barić, Ivo; Burlina, Alberto; Darin, Niklas; Hörster, Friederike; Coker, Mahmut; Ucar, Sema Kalkan; Krumina, Zita; Naess, Karin; Ngu, Lock H; Pronicka, Ewa; Riordan, Gilian; Santer, Rene; Wassmer, Evangeline; Zschocke, Johannes; Schiff, Manuel; de Meirleir, Linda; Alowain, Mohammed A; Smeitink, Jan A M; Morava, Eva; Kozicz, Tamas; Wevers, Ron A; Wolf, Nicole I; Willemsen, Michel A

2015-04-01

Pediatric movement disorders are still a diagnostic challenge, as many patients remain without a (genetic) diagnosis. Magnetic resonance imaging (MRI) pattern recognition can lead to the diagnosis. MEGDEL syndrome (3-MethylGlutaconic aciduria, Deafness, Encephalopathy, Leigh-like syndrome MIM #614739) is a clinically and biochemically highly distinctive dystonia deafness syndrome accompanied by 3-methylglutaconic aciduria, severe developmental delay, and progressive spasticity. Mutations are found in SERAC1, encoding a phosphatidylglycerol remodeling enzyme essential for both mitochondrial function and intracellular cholesterol trafficking. Based on the homogenous phenotype, we hypothesized an accordingly characteristic MRI pattern. A total of 43 complete MRI studies of 30 patients were systematically reevaluated. All patients presented a distinctive brain MRI pattern with five characteristic disease stages affecting the basal ganglia, especially the putamen. In stage 1, T2 signal changes of the pallidum are present. In stage 2, swelling of the putamen and caudate nucleus is seen. The dorsal putamen contains an "eye" that shows no signal alteration and (thus) seems to be spared during this stage of the disease. It later increases, reflecting progressive putaminal involvement. This "eye" was found in all patients with MEGDEL syndrome during a specific age range, and has not been reported in other disorders, making it pathognomonic for MEDGEL and allowing diagnosis based on MRI findings. Georg Thieme Verlag KG Stuttgart · New York.

Right ventricular functional analysis utilizing first pass radionuclide angiography for pre-operative ventricular assist device planning: a multi-modality comparison.

PubMed

Avery, Ryan; Day, Kevin; Jokerst, Clinton; Kazui, Toshinobu; Krupinski, Elizabeth; Khalpey, Zain

2017-10-10

Advanced heart failure treated with a left ventricular assist device is associated with a higher risk of right heart failure. Many advanced heart failures patients are treated with an ICD, a relative contraindication to MRI, prior to assist device placement. Given this limitation, left and right ventricular function for patients with an ICD is calculated using radionuclide angiography utilizing planar multigated acquisition (MUGA) and first pass radionuclide angiography (FPRNA), respectively. Given the availability of MRI protocols that can accommodate patients with ICDs, we have correlated the findings of ventricular functional analysis using radionuclide angiography to cardiac MRI, the reference standard for ventricle function calculation, to directly correlate calculated ejection fractions between these modalities, and to also assess agreement between available echocardiographic and hemodynamic parameters of right ventricular function. A retrospective review from January 2012 through May 2014 was performed to identify advanced heart failure patients who underwent both cardiac MRI and radionuclide angiography for ventricular functional analysis. Nine heart failure patients (8 men, 1 woman; mean age of 57.0 years) were identified. The average time between the cardiac MRI and radionuclide angiography exams was 38.9 days (range: 1 - 119 days). All patients undergoing cardiac MRI were scanned using an institutionally approved protocol for ICD with no device-related complications identified. A retrospective chart review of each patient for cardiomyopathy diagnosis, clinical follow-up, and echocardiogram and right heart catheterization performed during evaluation was also performed. The 9 patients demonstrated a mean left ventricular ejection fraction (LVEF) using cardiac MRI of 20.7% (12 - 40%). Mean LVEF using MUGA was 22.6% (12 - 49%). The mean right ventricular ejection fraction (RVEF) utilizing cardiac MRI was 28.3% (16 - 43%), and the mean RVEF calculated by FPRNA was 32.6% (9 - 56%). The mean discrepancy for LVEF between cardiac MRI and MUGA was 4.1% (0 - 9%), and correlation of calculated LVEF using cardiac MRI and MUGA demonstrated an R of 0.9. The mean discrepancy for RVEF between cardiac MRI and FPRNA was 12.0% (range: 2 - 24%) with a moderate correlation (R = 0.5). The increased discrepancies for RV analysis were statistically significant using an unpaired t-test (t = 3.19, p = 0.0061). Echocardiogram parameters of RV function, including TAPSE and FAC, were for available for all 9 patients and agreement with cardiac MRI demonstrated a kappa statistic for TAPSE of 0.39 (95% CI of 0.06 - 0.72) and for FAC of 0.64 (95% of 0.21 - 1.00). Heart failure patients are increasingly requiring left ventricular assist device placement; however, definitive evaluation of biventricular function is required due to the increased mortality rate associated with right heart failure after assist device placement. Our results suggest that FPRNA only has a moderate correlation with reference standard RVEFs calculated using cardiac MRI, which was similar to calculated agreements between cardiac MRI and echocardiographic parameters of right ventricular function. Given the need for identification of patients at risk for right heart failure, further studies are warranted to determine a more accurate estimate of RVEF for heart failure patients during pre-operative ventricular assist device planning.

Dynamic fMRI of a decision-making task

NASA Astrophysics Data System (ADS)

Singh, Manbir; Sungkarat, Witaya

2008-03-01

A novel fMRI technique has been developed to capture the dynamics of the evolution of brain activity during complex tasks such as those designed to evaluate the neural basis of decision-making under different situations. A task called the Iowa Gambling Task was used as an example. Six normal human volunteers were studied. The task was presented inside a 3T MRI and a dynamic fMRI study of the approximately 2s period between the beginning and end of the decision-making period was conducted by employing a series of reference functions, separated by 200 ms, designed to capture activation at different time-points within this period. As decision-making culminates with a button-press, the timing of the button press was chosen as the reference (t=0) and corresponding reference functions were shifted backward in steps of 200ms from this point up to the time when motor activity from the previous button press became predominant. SPM was used to realign, high-pass filter (cutoff 200s), normalize to the Montreal Neurological Institute (MNI) Template using a 12 parameter affine/non-linear transformation, 8mm Gaussian smoothing, and event-related General Linear Model analysis for each of the shifted reference functions. The t-score of each activated voxel was then examined to find its peaking time. A random effect analysis (p<0.05) showed prefrontal, parietal and bi-lateral hippocampal activation peaking at different times during the decision making period in the n=6 group study.

Neurochemical and BOLD responses during neuronal activation measured in the human visual cortex at 7 Tesla.

PubMed

Bednařík, Petr; Tkáč, Ivan; Giove, Federico; DiNuzzo, Mauro; Deelchand, Dinesh K; Emir, Uzay E; Eberly, Lynn E; Mangia, Silvia

2015-03-31

Several laboratories have consistently reported small concentration changes in lactate, glutamate, aspartate, and glucose in the human cortex during prolonged stimuli. However, whether such changes correlate with blood oxygenation level-dependent functional magnetic resonance imaging (BOLD-fMRI) signals have not been determined. The present study aimed at characterizing the relationship between metabolite concentrations and BOLD-fMRI signals during a block-designed paradigm of visual stimulation. Functional magnetic resonance spectroscopy (fMRS) and fMRI data were acquired from 12 volunteers. A short echo-time semi-LASER localization sequence optimized for 7 Tesla was used to achieve full signal-intensity MRS data. The group analysis confirmed that during stimulation lactate and glutamate increased by 0.26 ± 0.06 μmol/g (~30%) and 0.28 ± 0.03 μmol/g (~3%), respectively, while aspartate and glucose decreased by 0.20 ± 0.04 μmol/g (~5%) and 0.19 ± 0.03 μmol/g (~16%), respectively. The single-subject analysis revealed that BOLD-fMRI signals were positively correlated with glutamate and lactate concentration changes. The results show a linear relationship between metabolic and BOLD responses in the presence of strong excitatory sensory inputs, and support the notion that increased functional energy demands are sustained by oxidative metabolism. In addition, BOLD signals were inversely correlated with baseline γ-aminobutyric acid concentration. Finally, we discussed the critical importance of taking into account linewidth effects on metabolite quantification in fMRS paradigms.

Symmetric Positive 4th Order Tensors & Their Estimation from Diffusion Weighted MRI⋆

PubMed Central

Barmpoutis, Angelos; Jian, Bing; Vemuri, Baba C.; Shepherd, Timothy M.

2009-01-01

In Diffusion Weighted Magnetic Resonance Image (DW-MRI) processing a 2nd order tensor has been commonly used to approximate the diffusivity function at each lattice point of the DW-MRI data. It is now well known that this 2nd-order approximation fails to approximate complex local tissue structures, such as fibers crossings. In this paper we employ a 4th order symmetric positive semi-definite (PSD) tensor approximation to represent the diffusivity function and present a novel technique to estimate these tensors from the DW-MRI data guaranteeing the PSD property. There have been several published articles in literature on higher order tensor approximations of the diffusivity function but none of them guarantee the positive semi-definite constraint, which is a fundamental constraint since negative values of the diffusivity coefficients are not meaningful. In our methods, we parameterize the 4th order tensors as a sum of squares of quadratic forms by using the so called Gram matrix method from linear algebra and its relation to the Hilbert’s theorem on ternary quartics. This parametric representation is then used in a nonlinear-least squares formulation to estimate the PSD tensors of order 4 from the data. We define a metric for the higher-order tensors and employ it for regularization across the lattice. Finally, performance of this model is depicted on synthetic data as well as real DW-MRI from an isolated rat hippocampus. PMID:17633709

Combining anatomical, diffusion, and resting state functional magnetic resonance imaging for individual classification of mild and moderate Alzheimer's disease.

PubMed

Schouten, Tijn M; Koini, Marisa; de Vos, Frank; Seiler, Stephan; van der Grond, Jeroen; Lechner, Anita; Hafkemeijer, Anne; Möller, Christiane; Schmidt, Reinhold; de Rooij, Mark; Rombouts, Serge A R B

2016-01-01

Magnetic resonance imaging (MRI) is sensitive to structural and functional changes in the brain caused by Alzheimer's disease (AD), and can therefore be used to help in diagnosing the disease. Improving classification of AD patients based on MRI scans might help to identify AD earlier in the disease's progress, which may be key in developing treatments for AD. In this study we used an elastic net classifier based on several measures derived from the MRI scans of mild to moderate AD patients (N = 77) from the prospective registry on dementia study and controls (N = 173) from the Austrian Stroke Prevention Family Study. We based our classification on measures from anatomical MRI, diffusion weighted MRI and resting state functional MRI. Our unimodal classification performance ranged from an area under the curve (AUC) of 0.760 (full correlations between functional networks) to 0.909 (grey matter density). When combining measures from multiple modalities in a stepwise manner, the classification performance improved to an AUC of 0.952. This optimal combination consisted of grey matter density, white matter density, fractional anisotropy, mean diffusivity, and sparse partial correlations between functional networks. Classification performance for mild AD as well as moderate AD also improved when using this multimodal combination. We conclude that different MRI modalities provide complementary information for classifying AD. Moreover, combining multiple modalities can substantially improve classification performance over unimodal classification.

Defining functional SMA and pre-SMA subregions in human MFC using resting state fMRI: functional connectivity-based parcellation method.

PubMed

Kim, Jae-Hun; Lee, Jong-Min; Jo, Hang Joon; Kim, Sook Hui; Lee, Jung Hee; Kim, Sung Tae; Seo, Sang Won; Cox, Robert W; Na, Duk L; Kim, Sun I; Saad, Ziad S

2010-02-01

Noninvasive parcellation of the human cerebral cortex is an important goal for understanding and examining brain functions. Recently, the patterns of anatomical connections using diffusion tensor imaging (DTI) have been used to parcellate brain regions. Here, we present a noninvasive parcellation approach that uses "functional fingerprints" obtained by correlation measures on resting state functional magnetic resonance imaging (fMRI) data to parcellate brain regions. In other terms, brain regions are parcellated based on the similarity of their connection--as reflected by correlation during resting state--to the whole brain. The proposed method was used to parcellate the medial frontal cortex (MFC) into supplementary motor areas (SMA) and pre-SMA subregions. In agreement with anatomical landmark-based parcellation, we find that functional fingerprint clustering of the MFC results in anterior and posterior clusters. The probabilistic maps from 12 subjects showed that the anterior cluster is mainly located rostral to the vertical commissure anterior (VCA) line, whereas the posterior cluster is mainly located caudal to VCA line, suggesting the homologues of pre-SMA and SMA. The functional connections from the putative pre-SMA cluster were connected to brain regions which are responsible for complex/cognitive motor control, whereas those from the putative SMA cluster were connected to brain regions which are related to the simple motor control. These findings demonstrate the feasibility of the functional connectivity-based parcellation of the human cerebral cortex using resting state fMRI. Copyright (c) 2009 Elsevier Inc. All rights reserved.

Resting-state activity in development and maintenance of normal brain function.

PubMed

Pizoli, Carolyn E; Shah, Manish N; Snyder, Abraham Z; Shimony, Joshua S; Limbrick, David D; Raichle, Marcus E; Schlaggar, Bradley L; Smyth, Matthew D

2011-07-12

One of the most intriguing recent discoveries concerning brain function is that intrinsic neuronal activity manifests as spontaneous fluctuations of the blood oxygen level-dependent (BOLD) functional MRI signal. These BOLD fluctuations exhibit temporal synchrony within widely distributed brain regions known as resting-state networks. Resting-state networks are present in the waking state, during sleep, and under general anesthesia, suggesting that spontaneous neuronal activity plays a fundamental role in brain function. Despite its ubiquitous presence, the physiological role of correlated, spontaneous neuronal activity remains poorly understood. One hypothesis is that this activity is critical for the development of synaptic connections and maintenance of synaptic homeostasis. We had a unique opportunity to test this hypothesis in a 5-y-old boy with severe epileptic encephalopathy. The child developed marked neurologic dysfunction in association with a seizure disorder, resulting in a 1-y period of behavioral regression and progressive loss of developmental milestones. His EEG showed a markedly abnormal pattern of high-amplitude, disorganized slow activity with frequent generalized and multifocal epileptiform discharges. Resting-state functional connectivity MRI showed reduced BOLD fluctuations and a pervasive lack of normal connectivity. The child underwent successful corpus callosotomy surgery for treatment of drop seizures. Postoperatively, the patient's behavior returned to baseline, and he resumed development of new skills. The waking EEG revealed a normal background, and functional connectivity MRI demonstrated restoration of functional connectivity architecture. These results provide evidence that intrinsic, coherent neuronal signaling may be essential to the development and maintenance of the brain's functional organization.

Superresolution parallel magnetic resonance imaging: Application to functional and spectroscopic imaging

PubMed Central

Otazo, Ricardo; Lin, Fa-Hsuan; Wiggins, Graham; Jordan, Ramiro; Sodickson, Daniel; Posse, Stefan

2009-01-01

Standard parallel magnetic resonance imaging (MRI) techniques suffer from residual aliasing artifacts when the coil sensitivities vary within the image voxel. In this work, a parallel MRI approach known as Superresolution SENSE (SURE-SENSE) is presented in which acceleration is performed by acquiring only the central region of k-space instead of increasing the sampling distance over the complete k-space matrix and reconstruction is explicitly based on intra-voxel coil sensitivity variation. In SURE-SENSE, parallel MRI reconstruction is formulated as a superresolution imaging problem where a collection of low resolution images acquired with multiple receiver coils are combined into a single image with higher spatial resolution using coil sensitivities acquired with high spatial resolution. The effective acceleration of conventional gradient encoding is given by the gain in spatial resolution, which is dictated by the degree of variation of the different coil sensitivity profiles within the low resolution image voxel. Since SURE-SENSE is an ill-posed inverse problem, Tikhonov regularization is employed to control noise amplification. Unlike standard SENSE, for which acceleration is constrained to the phase-encoding dimension/s, SURE-SENSE allows acceleration along all encoding directions — for example, two-dimensional acceleration of a 2D echo-planar acquisition. SURE-SENSE is particularly suitable for low spatial resolution imaging modalities such as spectroscopic imaging and functional imaging with high temporal resolution. Application to echo-planar functional and spectroscopic imaging in human brain is presented using two-dimensional acceleration with a 32-channel receiver coil. PMID:19341804

The effect of hippocampal function, volume and connectivity on posterior cingulate cortex functioning during episodic memory fMRI in mild cognitive impairment.

PubMed

Papma, Janne M; Smits, Marion; de Groot, Marius; Mattace Raso, Francesco U; van der Lugt, Aad; Vrooman, Henri A; Niessen, Wiro J; Koudstaal, Peter J; van Swieten, John C; van der Veen, Frederik M; Prins, Niels D

2017-09-01

Diminished function of the posterior cingulate cortex (PCC) is a typical finding in early Alzheimer's disease (AD). It is hypothesized that in early stage AD, PCC functioning relates to or reflects hippocampal dysfunction or atrophy. The aim of this study was to examine the relationship between hippocampus function, volume and structural connectivity, and PCC activation during an episodic memory task-related fMRI study in mild cognitive impairment (MCI). MCI patients (n = 27) underwent episodic memory task-related fMRI, 3D-T1w MRI, 2D T2-FLAIR MRI and diffusion tensor imaging. Stepwise linear regression analysis was performed to examine the relationship between PCC activation and hippocampal activation, hippocampal volume and diffusion measures within the cingulum along the hippocampus. We found a significant relationship between PCC and hippocampus activation during successful episodic memory encoding and correct recognition in MCI patients. We found no relationship between the PCC and structural hippocampal predictors. Our results indicate a relationship between PCC and hippocampus activation during episodic memory engagement in MCI. This may suggest that during episodic memory, functional network deterioration is the most important predictor of PCC functioning in MCI. • PCC functioning during episodic memory relates to hippocampal functioning in MCI. • PCC functioning during episodic memory does not relate to hippocampal structure in MCI. • Functional network changes are an important predictor of PCC functioning in MCI.

funcLAB/G-service-oriented architecture for standards-based analysis of functional magnetic resonance imaging in HealthGrids.

PubMed

Erberich, Stephan G; Bhandekar, Manasee; Chervenak, Ann; Kesselman, Carl; Nelson, Marvin D

2007-01-01

Functional MRI is successfully being used in clinical and research applications including preoperative planning, language mapping, and outcome monitoring. However, clinical use of fMRI is less widespread due to its complexity of imaging, image workflow, post-processing, and lack of algorithmic standards hindering result comparability. As a consequence, wide-spread adoption of fMRI as clinical tool is low contributing to the uncertainty of community physicians how to integrate fMRI into practice. In addition, training of physicians with fMRI is in its infancy and requires clinical and technical understanding. Therefore, many institutions which perform fMRI have a team of basic researchers and physicians to perform fMRI as a routine imaging tool. In order to provide fMRI as an advanced diagnostic tool to the benefit of a larger patient population, image acquisition and image post-processing must be streamlined, standardized, and available at any institution which does not have these resources available. Here we describe a software architecture, the functional imaging laboratory (funcLAB/G), which addresses (i) standardized image processing using Statistical Parametric Mapping and (ii) its extension to secure sharing and availability for the community using standards-based Grid technology (Globus Toolkit). funcLAB/G carries the potential to overcome the limitations of fMRI in clinical use and thus makes standardized fMRI available to the broader healthcare enterprise utilizing the Internet and HealthGrid Web Services technology.

Pharmacological MRI in animal models: a useful tool for 5-HT research?

PubMed

Martin, Chris; Sibson, Nicola R

2008-11-01

Pharmacological magnetic resonance imaging (phMRI) offers the potential to provide novel insights into the functioning of neurotransmitter systems and drug action in the central nervous system. To date, much of the neuropharmacological research that has applied phMRI techniques has focused on the dopaminergic system with relatively few studies into serotonergic function. In this article, we discuss the current capabilities of, and future potential for phMRI to address fundamental questions in serotonergic research using animal models. Firstly we review existing literature on the application of phMRI to the serotonergic system by exploring 3 broad research themes: (i) the functional anatomy of the serotonergic system; (ii) drug-receptor targeting and distribution; and (iii) disease models and drug development. Subsequently, we discuss the interpretation of phMRI data in terms of neuropharmacological action with a focus on issues specific to neuroimaging studies of the serotonergic system. Unlike other neuroimaging approaches such as positron emission tomography, phMRI methods do not currently offer sensitivity to markers of specific pharmacological action. However, they can provide in vivo markers of the neuropharmacological modulation of neuronal activity across the whole brain with unparalleled spatial and temporal resolution. Furthermore, due to the non-invasive nature of MRI, these markers are readily translatable to human studies. Whilst there are a number of constraints and limitations to phMRI methods that necessitate careful data interpretation, we argue that phMRI could become a valuable research tool in neuropharmacological studies of the serotonergic system.

Functional MR imaging assessment of a non-responsive brain injured patient.

PubMed

Moritz, C H; Rowley, H A; Haughton, V M; Swartz, K R; Jones, J; Badie, B

2001-10-01

Functional magnetic resonance imaging (fMRI) was requested to assist in the evaluation of a comatose 38-year-old woman who had sustained multiple cerebral contusions from a motor vehicle accident. Previous electrophysiologic studies suggested absence of thalamocortical processing in response to median nerve stimulation. Whole-brain fMRI was performed utilizing visual, somatosensory, and auditory stimulation paradigms. Results demonstrated intact task-correlated sensory and cognitive blood oxygen level dependent (BOLD) hemodynamic response to stimuli. Electrodiagnostic studies were repeated and evoked potentials indicated supratentorial recovery in the cerebrum. At 3-months post trauma the patient had recovered many cognitive & sensorimotor functions, accurately reflecting the prognostic fMRI evaluation. These results indicate that fMRI examinations may provide a useful evaluation for brain function in non-responsive brain trauma patients.

Clinical Applications of Resting State Functional Connectivity

PubMed Central

Fox, Michael D.; Greicius, Michael

2010-01-01

During resting conditions the brain remains functionally and metabolically active. One manifestation of this activity that has become an important research tool is spontaneous fluctuations in the blood oxygen level-dependent (BOLD) signal of functional magnetic resonance imaging (fMRI). The identification of correlation patterns in these spontaneous fluctuations has been termed resting state functional connectivity (fcMRI) and has the potential to greatly increase the translation of fMRI into clinical care. In this article we review the advantages of the resting state signal for clinical applications including detailed discussion of signal to noise considerations. We include guidelines for performing resting state research on clinical populations, outline the different areas for clinical application, and identify important barriers to be addressed to facilitate the translation of resting state fcMRI into the clinical realm. PMID:20592951

MRI to assess renal structure and function.

PubMed

Artunc, Ferruh; Rossi, Cristina; Boss, Andreas

2011-11-01

In addition to excellent anatomical depiction, MRI techniques have expanded to study functional aspects of renal physiology, such as renal perfusion, glomerular filtration rate (GFR) or tissue oxygenation. This review will focus on current developments with an emphasis on clinical applicability. The method of GFR determination is largely heterogeneous and still has weaknesses. However, the technique of employing liver disappearance curves has been shown to be accurate in healthy persons and patients with chronic kidney disease. In potential kidney donors, complete evaluation of kidney anatomy and function can be accomplished in a single-stop investigation. Techniques without contrast media can be utilized to measure renal tissue oxygenation (blood oxygen level-dependent MRI) or perfusion (arterial spin labeling) and could aid in the diagnosis and treatment of ischemic renal diseases, such as renal artery stenosis. Diffusion imaging techniques may provide information on spatially restricted water diffusion and tumor cellularity. Functional MRI opens new horizons in studying renal physiology and pathophysiology in vivo. Although extensively utilized in research, labor-intensive postprocessing and lack of standardization currently limit the clinical applicability of functional MRI. Further studies are necessary to evaluate the clinical value of functional magnetic resonance techniques for early discovery and characterization of kidney disease.

Awake Craniotomy for Tumor Resection: Further Optimizing Therapy of Brain Tumors.

PubMed

Mehdorn, H Maximilian; Schwartz, Felix; Becker, Juliane

2017-01-01

In recent years more and more data have emerged linking the most radical resection to prolonged survival in patients harboring brain tumors. Since total tumor resection could increase postoperative morbidity, many methods have been suggested to reduce the risk of postoperative neurological deficits: awake craniotomy with the possibility of continuous patient-surgeon communication is one of the possibilities of finding out how radical a tumor resection can possibly be without causing permanent harm to the patient.In 1994 we started to perform awake craniotomy for glioma resection. In 2005 the use of intraoperative high-field magnetic resonance imaging (MRI) was included in the standard tumor therapy protocol. Here we review our experience in performing awake surgery for gliomas, gained in 219 patients.Patient selection by the operating surgeon and a neuropsychologist is of primary importance: the patient should feel as if they are part of the surgical team fighting against the tumor. The patient will undergo extensive neuropsychological testing, functional MRI, and fiber tractography in order to define the relationship between the tumor and the functionally relevant brain areas. Attention needs to be given at which particular time during surgery the intraoperative MRI is performed. Results from part of our series (without and with ioMRI scan) are presented.

Resting states are resting traits--an FMRI study of sex differences and menstrual cycle effects in resting state cognitive control networks.

PubMed

Hjelmervik, Helene; Hausmann, Markus; Osnes, Berge; Westerhausen, René; Specht, Karsten

2014-01-01

To what degree resting state fMRI is stable or susceptible to internal mind states of the individual is currently an issue of debate. To address this issue, the present study focuses on sex differences and investigates whether resting state fMRI is stable in men and women or changes within relative short-term periods (i.e., across the menstrual cycle). Due to the fact that we recently reported menstrual cycle effects on cognitive control based on data collected during the same sessions, the current study is particularly interested in fronto-parietal resting state networks. Resting state fMRI was measured in sixteen women during three different cycle phases (menstrual, follicular, and luteal). Fifteen men underwent three sessions in corresponding time intervals. We used independent component analysis to identify four fronto-parietal networks. The results showed sex differences in two of these networks with women exhibiting higher functional connectivity in general, including the prefrontal cortex. Menstrual cycle effects on resting states were non-existent. It is concluded that sex differences in resting state fMRI might reflect sexual dimorphisms in the brain rather than transitory activating effects of sex hormones on the functional connectivity in the resting brain.

A general dual-bolus approach for quantitative DCE-MRI.

PubMed

Kershaw, Lucy E; Cheng, Hai-Ling Margaret

2011-02-01

To present a dual-bolus technique for quantitative dynamic contrast-enhanced MRI (DCE-MRI) and show that it can give an arterial input function (AIF) measurement equivalent to that from a single-bolus protocol. Five rabbits were imaged using a dual-bolus technique applicable for high-resolution DCE-MRI, incorporating a time resolved imaging of contrast kinetics (TRICKS) sequence for rapid temporal sampling. AIFs were measured from both the low-dose prebolus and the high-dose main bolus in the abdominal aorta. In one animal, TRICKS and fast spoiled gradient echo (FSPGR) acquisitions were compared. The scaled prebolus AIF was shown to match the main bolus AIF, with 95% confidence intervals overlapping for fits of gamma-variate functions to the first pass and linear fits to the washout phase, with the exception of one case. The AIFs measured using TRICKS and FSPGR were shown to be equivalent in one animal. The proposed technique can capture even the rapid circulation kinetics in the rabbit aorta, and the scaled prebolus AIF is equivalent to the AIF from a high-dose injection. This allows separate measurements of the AIF and tissue uptake curves, meaning that each curve can then be acquired using a protocol tailored to its specific requirements. Copyright © 2011 Elsevier Inc. All rights reserved.

A novel tablet computer platform for advanced language mapping during awake craniotomy procedures.

PubMed

Morrison, Melanie A; Tam, Fred; Garavaglia, Marco M; Golestanirad, Laleh; Hare, Gregory M T; Cusimano, Michael D; Schweizer, Tom A; Das, Sunit; Graham, Simon J

2016-04-01

A computerized platform has been developed to enhance behavioral testing during intraoperative language mapping in awake craniotomy procedures. The system is uniquely compatible with the environmental demands of both the operating room and preoperative functional MRI (fMRI), thus providing standardized testing toward improving spatial agreement between the 2 brain mapping techniques. Details of the platform architecture, its advantages over traditional testing methods, and its use for language mapping are described. Four illustrative cases demonstrate the efficacy of using the testing platform to administer sophisticated language paradigms, and the spatial agreement between intraoperative mapping and preoperative fMRI results. The testing platform substantially improved the ability of the surgeon to detect and characterize language deficits. Use of a written word generation task to assess language production helped confirm areas of speech apraxia and speech arrest that were inadequately characterized or missed with the use of traditional paradigms, respectively. Preoperative fMRI of the analogous writing task was also assistive, displaying excellent spatial agreement with intraoperative mapping in all 4 cases. Sole use of traditional testing paradigms can be limiting during awake craniotomy procedures. Comprehensive assessment of language function will require additional use of more sophisticated and ecologically valid testing paradigms. The platform presented here provides a means to do so.

Functional magnetic resonance imaging activation detection: fuzzy cluster analysis in wavelet and multiwavelet domains.

PubMed

Jahanian, Hesamoddin; Soltanian-Zadeh, Hamid; Hossein-Zadeh, Gholam-Ali

2005-09-01

To present novel feature spaces, based on multiscale decompositions obtained by scalar wavelet and multiwavelet transforms, to remedy problems associated with high dimension of functional magnetic resonance imaging (fMRI) time series (when they are used directly in clustering algorithms) and their poor signal-to-noise ratio (SNR) that limits accurate classification of fMRI time series according to their activation contents. Using randomization, the proposed method finds wavelet/multiwavelet coefficients that represent the activation content of fMRI time series and combines them to define new feature spaces. Using simulated and experimental fMRI data sets, the proposed feature spaces are compared to the cross-correlation (CC) feature space and their performances are evaluated. In these studies, the false positive detection rate is controlled using randomization. To compare different methods, several points of the receiver operating characteristics (ROC) curves, using simulated data, are estimated and compared. The proposed features suppress the effects of confounding signals and improve activation detection sensitivity. Experimental results show improved sensitivity and robustness of the proposed method compared to the conventional CC analysis. More accurate and sensitive activation detection can be achieved using the proposed feature spaces compared to CC feature space. Multiwavelet features show superior detection sensitivity compared to the scalar wavelet features. (c) 2005 Wiley-Liss, Inc.

Automatic Segmenting Structures in MRI's Based on Texture Analysis and Fuzzy Logic

NASA Astrophysics Data System (ADS)

Kaur, Mandeep; Rattan, Munish; Singh, Pushpinder

2017-12-01

The purpose of this paper is to present the variational method for geometric contours which helps the level set function remain close to the sign distance function, therefor it remove the need of expensive re-initialization procedure and thus, level set method is applied on magnetic resonance images (MRI) to track the irregularities in them as medical imaging plays a substantial part in the treatment, therapy and diagnosis of various organs, tumors and various abnormalities. It favors the patient with more speedy and decisive disease controlling with lesser side effects. The geometrical shape, the tumor's size and tissue's abnormal growth can be calculated by the segmentation of that particular image. It is still a great challenge for the researchers to tackle with an automatic segmentation in the medical imaging. Based on the texture analysis, different images are processed by optimization of level set segmentation. Traditionally, optimization was manual for every image where each parameter is selected one after another. By applying fuzzy logic, the segmentation of image is correlated based on texture features, to make it automatic and more effective. There is no initialization of parameters and it works like an intelligent system. It segments the different MRI images without tuning the level set parameters and give optimized results for all MRI's.

Experimental MRI-SPECT insert system with Hybrid Semiconductor detectors Timepix for MR animal scanner Bruker 47/20

NASA Astrophysics Data System (ADS)

Zajicek, J.; Burian, M.; Soukup, P.; Novak, V.; Macko, M.; Jakubek, J.

2017-01-01

Multimodal medical imaging based on Magnetic Resonance is mainly combinated with one of the scintigraphic method like PET or SPECT. These methods provide functional information whereas magnetic resonance imaging provides high spatial resolution of anatomical information or complementary functional information. Fusion of imaging modalities allows researchers to obtain complimentary information in a single measurement. The combination of MRI with SPECT is still relatively new and challenging in many ways. The main complication of using SPECT in MRI systems is the presence of a high magnetic field therefore (ferro)magnetic materials have to be eliminated. Furthermore the application of radiofrequency fields within the MR gantry does not allow for the use of conductive structures such as the common heavy metal collimators. This work presents design and construction of an experimental MRI-SPECT insert system and its initial tests. This unique insert system consists of an MR-compatible SPECT setup with CdTe pixelated sensors Timepix tungsten collimators and a radiofrequency coil. Measurements were performed on a gelatine and tissue phantom with an embedded radioisotopic source (57Co 122 keV γ ray) inside the RF coil by the Bruker BioSpec 47/20 (4.7 T) MR animal scanner. The project was performed in the framework of the Medipix Collaboration.

Impact of functional magnetic resonance imaging (fMRI) scanner noise on affective state and attentional performance.

PubMed

Jacob, Shawna N; Shear, Paula K; Norris, Matthew; Smith, Matthew; Osterhage, Jeff; Strakowski, Stephen M; Cerullo, Michael; Fleck, David E; Lee, Jing-Huei; Eliassen, James C

2015-01-01

Previous research has shown that performance on cognitive tasks administered in the scanner can be altered by the scanner environment. There are no previous studies that have investigated the impact of scanner noise using a well-validated measure of affective change. The goal of this study was to determine whether performance on an affective attentional task or emotional response to the task would change in the presence of distracting acoustic noise, such as that encountered in a magnetic resonance imaging (MRI) environment. Thirty-four young adults with no self-reported history of neurologic disorder or mental illness completed three blocks of the affective Posner task outside of the scanner. The task was meant to induce frustration through monetary contingencies and rigged feedback. Participants completed a Self-Assessment Manikin at the end of each block to rate their mood, arousal level, and sense of dominance. During the task, half of the participants heard noise (recorded from a 4T MRI system), and half heard no noise. The affective Posner task led to significant reductions in mood and increases in arousal in healthy participants. The presence of scanner noise did not impact task performance; however, individuals in the noise group did report significantly poorer mood throughout the task. The results of the present study suggest that the acoustic qualities of MRI enhance frustration effects on an affective attentional task and that scanner noise may influence mood during similar functional magnetic resonance imaging (fMRI) tasks.

Electrophysiological correlates of the BOLD signal for EEG-informed fMRI

PubMed Central

Murta, Teresa; Leite, Marco; Carmichael, David W; Figueiredo, Patrícia; Lemieux, Louis

2015-01-01

Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are important tools in cognitive and clinical neuroscience. Combined EEG–fMRI has been shown to help to characterise brain networks involved in epileptic activity, as well as in different sensory, motor and cognitive functions. A good understanding of the electrophysiological correlates of the blood oxygen level-dependent (BOLD) signal is necessary to interpret fMRI maps, particularly when obtained in combination with EEG. We review the current understanding of electrophysiological–haemodynamic correlates, during different types of brain activity. We start by describing the basic mechanisms underlying EEG and BOLD signals and proceed by reviewing EEG-informed fMRI studies using fMRI to map specific EEG phenomena over the entire brain (EEG–fMRI mapping), or exploring a range of EEG-derived quantities to determine which best explain colocalised BOLD fluctuations (local EEG–fMRI coupling). While reviewing studies of different forms of brain activity (epileptic and nonepileptic spontaneous activity; cognitive, sensory and motor functions), a significant attention is given to epilepsy because the investigation of its haemodynamic correlates is the most common application of EEG-informed fMRI. Our review is focused on EEG-informed fMRI, an asymmetric approach of data integration. We give special attention to the invasiveness of electrophysiological measurements and the simultaneity of multimodal acquisitions because these methodological aspects determine the nature of the conclusions that can be drawn from EEG-informed fMRI studies. We emphasise the advantages of, and need for, simultaneous intracranial EEG–fMRI studies in humans, which recently became available and hold great potential to improve our understanding of the electrophysiological correlates of BOLD fluctuations. PMID:25277370

What can spontaneous fluctuations of the blood oxygenation-level-dependent signal tell us about psychiatric disorders?

PubMed

Fornito, Alex; Bullmore, Edward T

2010-05-01

Resting-state functional MRI (rs-fMRI) is an increasingly popular technique for studying brain dysfunction in psychiatric patients, and is widely assumed to measure intrinsic properties of functional brain organization. Here, we review rs-fMRI studies of psychiatric populations and consider how recent evidence concerning the neuronal basis, behavioural relevance, and the stability of rs-fMRI measures can inform and constrain interpretation of findings obtained using case-control designs. A range of rs-fMRI measures have been applied to different patient groups, although the findings have not always been consistent. The large-scale organization of rs-fMRI networks is robust and reproducible, and rs-fMRI measures show correlations with behavioural phenotypes relevant to psychiatry. However, evidence that such measures are also influenced by preceding psychological states and contexts, as well as individual variations in physiological arousal, may help to explain inconsistent findings in case-control comparisons. rs-fMRI measures show both stable and dynamic properties, the nature of which are only beginning to be uncovered. As such, interpreting significant differences between patients and controls on rs-fMRI measures as evidence for alterations in intrinsic functional brain organization should be done cautiously. Better understanding of the relationship between stable and transient aspects of spontaneous brain dynamics will be necessary to constrain interpretation of case-control studies and inform pathophysiological models.

Functional Imaging Signature of Patients Presenting with Polycythemia/Paraganglioma Syndromes.

PubMed

Janssen, Ingo; Chen, Clara C; Zhuang, Zhenping; Millo, Corina M; Wolf, Katherine I; Ling, Alexander; Lin, Frank I; Adams, Karen T; Herscovitch, Peter; Feelders, Richard A; Fojo, Antonio T; Taieb, David; Kebebew, Electron; Pacak, Karel

2017-08-01

Pheochromocytoma/paraganglioma (PPGL) syndromes associated with polycythemia have previously been described in association with mutations in the von Hippel-Lindau gene. Recently, mutations in the prolyl hydroxylase gene ( PHD ) 1 and 2 and in the hypoxia-inducible factor 2 α ( HIF2A ) were also found to be associated with multiple and recurrent PPGL. Such patients also presented with PPGL and polycythemia, and later on, some presented with duodenal somatostatinoma. In additional patients presenting with PPGL and polycythemia, no further mutations have been discovered. Because the functional imaging signature of patients with PPGL-polycythemia syndromes is still unknown, and because these tumors (in most patients) are multiple, recurrent, and metastatic, the goal of our study was to assess the optimal imaging approach using 4 different PET radiopharmaceuticals and CT/MRI in these patients. Methods: Fourteen patients (10 women, 4 men) with confirmed PPGL and polycythemia prospectively underwent 68 Ga-DOTATATE (13 patients), 18 F-FDG (13 patients), 18 F-fluorodihydroxyphenylalanine ( 18 F-FDOPA) (14 patients), 18 F-fluorodopamine ( 18 F-FDA) (11 patients), and CT/MRI (14 patients). Detection rates of PPGL lesions were compared between all imaging studies and stratified between the underlying mutations. Results: 18 F-FDOPA and 18 F-FDA PET/CT showed similar combined lesion-based detection rates of 98.7% (95% confidence interval [CI], 92.7%-99.8%) and 98.3% (95% CI, 90.9%-99.7%), respectively. The detection rates for 68 Ga-DOTATATE (35.3%; 95% CI, 25.0%-47.2%), 18 F-FDG (42.3; 95% CI, 29.9%-55.8%), and CT/MRI (60.3%; 95% CI, 48.8%-70.7%) were significantly lower ( P < 0.01), irrespective of the mutation status. Conclusion: 18 F-FDOPA and 18 F-FDA are superior to 18 F-FDG, 68 Ga-DOTATATE, and CT/MRI and should be the radiopharmaceuticals of choice in this rare group of patients. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.

Modality Specific Cerebro-Cerebellar Activations in Verbal Working Memory: An fMRI Study

PubMed Central

Kirschen, Matthew P.; Chen, S. H. Annabel; Desmond, John E.

2010-01-01

Verbal working memory (VWM) engages frontal and temporal/parietal circuits subserving the phonological loop, as well as, superior and inferior cerebellar regions which have projections from these neocortical areas. Different cerebro-cerebellar circuits may be engaged for integrating aurally- and visually-presented information for VWM. The present fMRI study investigated load (2, 4, or 6 letters) and modality (auditory and visual) dependent cerebro-cerebellar VWM activation using a Sternberg task. FMRI revealed modality-independent activations in left frontal (BA 6/9/44), insular, cingulate (BA 32), and bilateral inferior parietal/supramarginal (BA 40) regions, as well as in bilateral superior (HVI) and right inferior (HVIII) cerebellar regions. Visual presentation evoked prominent activations in right superior (HVI/CrusI) cerebellum, bilateral occipital (BA19) and left parietal (BA7/40) cortex while auditory presentation showed robust activations predominately in bilateral temporal regions (BA21/22). In the cerebellum, we noted a visual to auditory emphasis of function progressing from superior to inferior and from lateral to medial regions. These results extend our previous findings of fMRI activation in cerebro-cerebellar networks during VWM, and demonstrate both modality dependent commonalities and differences in activations with increasing memory load. PMID:20714061

Modality specific cerebro-cerebellar activations in verbal working memory: an fMRI study.

PubMed

Kirschen, Matthew P; Chen, S H Annabel; Desmond, John E

2010-01-01

Verbal working memory (VWM) engages frontal and temporal/parietal circuits subserving the phonological loop, as well as, superior and inferior cerebellar regions which have projections from these neocortical areas. Different cerebro-cerebellar circuits may be engaged for integrating aurally- and visually-presented information for VWM. The present fMRI study investigated load (2, 4, or 6 letters) and modality (auditory and visual) dependent cerebro-cerebellar VWM activation using a Sternberg task. FMRI revealed modality-independent activations in left frontal (BA 6/9/44), insular, cingulate (BA 32), and bilateral inferior parietal/supramarginal (BA 40) regions, as well as in bilateral superior (HVI) and right inferior (HVIII) cerebellar regions. Visual presentation evoked prominent activations in right superior (HVI/CrusI) cerebellum, bilateral occipital (BA19) and left parietal (BA7/40) cortex while auditory presentation showed robust activations predominantly in bilateral temporal regions (BA21/22). In the cerebellum, we noted a visual to auditory emphasis of function progressing from superior to inferior and from lateral to medial regions. These results extend our previous findings of fMRI activation in cerebro-cerebellar networks during VWM, and demonstrate both modality dependent commonalities and differences in activations with increasing memory load.

Multi- and Unisensory Decoding of Words and Nonwords Result in Differential Brain Responses in Dyslexic and Nondyslexic Adults

ERIC Educational Resources Information Center

Kast, Monika; Bezzola, Ladina; Jancke, Lutz; Meyer, Martin

2011-01-01

The present functional magnetic resonance imaging (fMRI) study was designed, in order to investigate the neural substrates involved in the audiovisual processing of disyllabic German words and pseudowords. Twelve dyslexic and 13 nondyslexic adults performed a lexical decision task while stimuli were presented unimodally (either aurally or…

Dynamic gadoxetate-enhanced MRI for the assessment of total and segmental liver function and volume in primary sclerosing cholangitis.

PubMed

Nilsson, Henrik; Blomqvist, Lennart; Douglas, Lena; Nordell, Anders; Jacobsson, Hans; Hagen, Karin; Bergquist, Annika; Jonas, Eduard

2014-04-01

To evaluate dynamic hepatocyte-specific contrast-enhanced MRI (DHCE-MRI) for the assessment of global and segmental liver volume and function in patients with primary sclerosing cholangitis (PSC), and to explore the heterogeneous distribution of liver function in this patient group. Twelve patients with primary sclerosing cholangitis (PSC) and 20 healthy volunteers were examined using DHCE-MRI with Gd-EOB-DTPA. Segmental and total liver volume were calculated, and functional parameters (hepatic extraction fraction [HEF], input relative blood-flow [irBF], and mean transit time [MTT]) were calculated in each liver voxel using deconvolutional analysis. In each study subject, and incongruence score (IS) was constructed to describe the mismatch between segmental function and volume. Among patients, the liver function parameters were correlated to bile duct obstruction and to established scoring models for liver disease. Liver function was significantly more heterogeneously distributed in the patient group (IS 1.0 versus 0.4). There were significant correlations between biliary obstruction and segmental functional parameters (HEF rho -0.24; irBF rho -0.45), and the Mayo risk score correlated significantly with the total liver extraction capacity of Gd-EOB-DTPA (rho -0.85). The study demonstrates a new method to quantify total and segmental liver function using DHCE-MRI in patients with PSC. Copyright © 2013 Wiley Periodicals, Inc.

Voluntary switching between identities in dissociative identity disorder: A functional MRI case study.

PubMed

Savoy, R L; Frederick, B B; Keuroghlian, A S; Wolk, P C

2012-01-01

Patients who suffer from dissociative identity disorder present unique scientific and clinical challenges for psychology and psychiatry. We have been fortunate in working with a patient who-while undergoing functional MRI-can switch rapidly and voluntarily between her main personality (a middle-aged, high-functioning woman) and an alternate personality (a 4-6-year-old girl). A unique task was designed to isolate the processes occurring during the switches between these personalities. Data are from two imaging sessions, conducted months apart, each showing the same activated areas during switches between these personalities. The activated areas include the following: the primary sensory and motor cortex, likely associated with characteristic facial movements made during switching; the nucleus accumbens bilaterally, possibly associated with aspects of reward connected with switching; and prefrontal sites, presumably associated with the executive control involved in the switching of personalities.