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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: S. Soloukey; E. Collée; L. Verhoef; D.D. Satoer; +10 Authors

    Accurate, depth-resolved functional imaging is key in both understanding and treatment of the human brain. A new sonography-based imaging technique named functional Ultrasound (fUS) uniquely combines high sensitivity with submillimeter-subsecond spatiotemporal resolution available in large fields-of-view. In this proof-of-concept study we show that: (A) fUS reveals the same eloquent regions as found by fMRI while concomitantly visualizing in-vivo microvascular morphology underlying these functional hemodynamics and (B) fUS-based functional maps are confirmed by Electrocortical Stimulation Mapping (ESM), the current gold-standard in awake neurosurgical practice. This unique cross-modality experiment was performed using motor, visual and language-related functional tasks in patients undergoing awake brain tumor resection. The current work serves as an important milestone towards further maturity of fUS as well as a novel avenue to increase our understanding of hemodynamics-based functional brain imaging.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ NeuroImagearrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    NeuroImage
    Article . 2023
    Data sources: DOAJ
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    NeuroImage
    Article . 2023
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    NeuroImage
    Article . 2023
    Data sources: KNAW Pure
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    NeuroImage
    Article . 2023 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ NeuroImagearrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      NeuroImage
      Article . 2023
      Data sources: DOAJ
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      NeuroImage
      Article . 2023
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      NeuroImage
      Article . 2023
      Data sources: KNAW Pure
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      NeuroImage
      Article . 2023 . Peer-reviewed
      License: CC BY
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    Authors: Bellomo, A; McGuire, P; Papagni, SA; Mechelli, A; +9 Authors

    Recent studies have identified DAAO as a probable susceptibility gene for schizophrenia and bipolar disorder. However, little is known about how this gene affects brain function to increase vulnerability to these disorders. We examined the impact of DAAO genotype (rs3918346) on brain function in patients with schizophrenia, patients with bipolar I disorder and healthy controls. We tested the hypothesis that a variation in DAAO genotype would be associated with altered prefrontal function and altered functional connectivity in schizophrenia and bipolar disorder. We used functional magnetic resonance imaging to measure brain responses during a verbal fluency task in a total of 121 subjects comprising 40 patients with schizophrenia, 33 patients with bipolar disorder and 48 healthy volunteers. We then used statistical parametric mapping (SPM) and psycho-physiological interaction (PPI) analyses to estimate the main effects of diagnostic group, the main effect of genotype, and their interaction on brain activation and on functional connectivity. Inferences were made at p < 0.05, after correction for multiple comparisons across the whole brain. In the schizophrenia group relative to the control group, patients with one or two copies of the T allele showed lower deactivation in the left precuneus and greater activation in the right posterior cingulate gyrus than patients with two copies of the C allele. This diagnosis × genotype interaction was associated with differences in the functional connectivity of these two regions with other cortical and subcortical areas. In contrast, there were no significant effects of diagnosis or of genotype in comparisons involving bipolar patients. Our results suggest that genetic variation in DAAO has a significant impact on both regional activation and functional connectivity, and provide evidence for a diagnosis-dependent pattern of gene action. © 2011 Elsevier Inc. link_to_subscribed_fulltext

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ NeuroImagearrow_drop_down
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    NeuroImage
    Article . 2010
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    NeuroImage
    Article . 2011 . Peer-reviewed
    License: Elsevier TDM
    Data sources: Crossref
    HKU Scholars Hub
    Article . 2011
    Data sources: HKU Scholars Hub
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ NeuroImagearrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      NeuroImage
      Article . 2010
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      NeuroImage
      Article . 2011 . Peer-reviewed
      License: Elsevier TDM
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      HKU Scholars Hub
      Article . 2011
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: van Eijsden, Pieter; Hyder, Fahmeed; Rothman, Douglas L.; Shulman, Robert G.;

    The successes of PET and fMRI in non-invasively localizing sensory functions had encouraged efforts to transform the subjective concepts of cognitive psychology into objective physical measures. The assumption was that mental functions could be decomposed into non-overlapping, context-independent modules that are operated on by separable areas of a computer-like brain. The failures of cognitive modularity and of a very localized phrenology are generally, but not universally, accepted; but in their place, and usually not distinguished from the original revolutionary hopes of clarification, experimental results are being interpreted in terms of rather flexible definitions of both cognitive concepts and the degree of localization. In an alternative approach, we have connected fMRI, (13)C MRS, and electrophysiology measurements of brain energy to connect with observable properties of mental life (i.e., awareness). We illustrate this approach with a sensory stimulation experiment; the degree of localization found in BOLD signals was related to the global energy of the brain which, when manipulated by anesthetics, affected the degree of awareness. The influence of brain energy upon functional imaging maps is changing the interpretations of neuroimaging experiments, from psychological concepts generating computer-like responses to empirical responses dominated by the high brain energy and signaling at rest. In our view "baseline" is an operational term, an adjective that defines a property of a state of the system before it is perturbed by a stimulus. Given the dependence of observable psychological properties upon the "baseline" energy, we believe that it is unnecessarily limiting to de. ne a particular state as the baseline. (C) 2008 Elsevier Inc. All rights reserved.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ NeuroImagearrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    NeuroImage
    Article . 2009
    Data sources: NARCIS
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    Europe PubMed Central
    Other literature type . 2008
    Data sources: PubMed Central
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    NeuroImage
    Article . 2009 . Peer-reviewed
    License: Elsevier TDM
    Data sources: Crossref
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    NeuroImage
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    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    NARCIS
    Article . 2009
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ NeuroImagearrow_drop_down
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      NeuroImage
      Article . 2009
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      Europe PubMed Central
      Other literature type . 2008
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      NeuroImage
      Article . 2009 . Peer-reviewed
      License: Elsevier TDM
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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      Article . 2009
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Hans, Olsson; Christer, Halldin; Lars, Farde;

    Dopaminergic neurotransmission in extrastriatal regions may play a crucial role in the pathophysiology and treatment of neuropsychiatric disorders. The high-affinity radioligands [(11)C]FLB 457, [(123)I]epidepride, and [(18)F]fallypride are now used in clinical studies to measure these low-density receptor populations in vivo. However, a single determination of the regional binding potential (BP) does not differentiate receptor density (B(max)) from the apparent affinity (K(D)). In this positron emission tomography (PET) study, we measured extrastriatal dopamine D2 receptor density (B(max)) and apparent affinity (K(D)) in 10 healthy subjects using an in vivo saturation approach. Each subject participated in two to three PET measurements with different specific radioactivity of [(11)C]FLB 457. The commonly used simplified reference tissue model (SRTM) was used in a comparison of BP values with the B(max) values obtained from the saturation analysis. The calculated regional receptor density values were of the same magnitude (0.33-1.68 nM) and showed the same rank order as reported from postmortem studies, that is, in descending order thalamus, lateral temporal cortex, anterior cinguli, and frontal cortex. The affinity ranged from 0.27 to 0.43 nM, that is, approximately 10-20 times the value found in vitro (20 pM). The area under the cerebellar time activity curve (TAC) was slightly lower (11 +/- 8%, mean +/- SD, P = 0.004, n = 10) after injection of low as compared with high specific radioactivity, indicating sensitivity to the minute density of dopamine D2 receptors in the this region. The results of the present study support that dopamine D2 receptor density and affinity can be differentiated in low-density regions using a saturation approach. There was a significant (P < 0.001) correlation between the binding potential calculated with SRTM and the receptor density (B(max)), which supports the use of BP in clinical studies where differentiation of B(max) and K(D) is not required. In such studies, the mass of FLB 457 has to be less than 0.5 microg injected to avoid a mass effect of the radioligand itself.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ NeuroImagearrow_drop_down
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    NeuroImage
    Article . 2003
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    NeuroImage
    Article . 2004 . Peer-reviewed
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      NeuroImage
      Article . 2003
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      NeuroImage
      Article . 2004 . Peer-reviewed
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    Authors: Ciuciu, Philippe; Abry, Patrice; He, Biyu Jade;

    Studies employing functional connectivity-type analyses have established that sponta-neous fluctuations in functional magnetic resonance imaging (fMRI) signals are orga-nized 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 univari-ate 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 fre-quencies 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 Rev.#1, Q5 International audience

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    NeuroImage
    Article . 2014 . Peer-reviewed
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    Europe PubMed Central
    Other literature type . 2014
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      NeuroImage
      Article . 2014 . Peer-reviewed
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      Europe PubMed Central
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    Authors: Peter Klaver; Armin de Greiff; Jürgen Fell; Jürgen Ruhlmann; +3 Authors
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    NeuroImage
    Article . 2001 . Peer-reviewed
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      Article . 2001 . Peer-reviewed
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    Authors: Caroline Presseau; Pierre-Marc Jodoin; Jean-Christophe Houde; Maxime Descoteaux;

    A single diffusion MRI streamline fiber tracking dataset may contain hundreds of thousands, and often millions of streamlines and can take up to several gigabytes of memory. This amount of data is not only heavy to compute, but also difficult to visualize and hard to store on disk (especially when dealing with a collection of brains). These problems call for a fiber-specific compression format that simplifies its manipulation. As of today, no fiber compression format has yet been adopted and the need for it is now becoming an issue for future connectomics research. In this work, we propose a new compression format, .zfib, for streamline tractography datasets reconstructed from diffusion magnetic resonance imaging (dMRI). Tracts contain a large amount of redundant information and are relatively smooth. Hence, they are highly compressible. The proposed method is a processing pipeline containing a linearization, a quantization and an encoding step. Our pipeline is tested and validated under a wide range of DTI and HARDI tractography configurations (step size, streamline number, deterministic and probabilistic tracking) and compression options. Similar to JPEG, the user has one parameter to select: a worst-case maximum tolerance error in millimeter (mm). Overall, we find a compression factor of more than 96% for a maximum error of 0.1mm without any perceptual change or change of diffusion statistics (mean fractional anisotropy and mean diffusivity) along bundles. This opens new opportunities for connectomics and tractometry applications.

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    Article . 2014
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    NeuroImage
    Article . 2015 . Peer-reviewed
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      Article . 2014
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      NeuroImage
      Article . 2015 . Peer-reviewed
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    Authors: De Luca, Alberto; Guo, Fenghua; Froeling, Martijn; Leemans, Alexander;

    AbstractIn diffusion MRI, spherical deconvolution approaches can estimate local white matter (WM) fiber orientation distributions (FOD) which can be used to produce fiber tractography reconstructions. The applicability of spherical deconvolution to grey matter (GM), however, is still limited, despite its critical role as start/endpoint of WM fiber pathways. The advent of multi-shell diffusion MRI data offers additional contrast to model the GM signal but, to date, only isotropic models have been applied to GM. Evidence from both histology and high-resolution diffusion MRI studies suggests a marked anisotropic character of the diffusion process in GM, which could be exploited to improve the description of the cortical organization. In this study, we investigated whether performing spherical deconvolution with tissue specific models of both WM and GM can improve the characterization of the latter while retaining state-of-the-art performances in WM. To this end, we developed a framework able to simultaneously accommodate multiple anisotropic response functions to estimate multiple, tissue-specific, fiber orientation distributions (mFODs). As proof of principle, we used the diffusion kurtosis imaging model to represent the WM signal, and the neurite orientation dispersion and density imaging (NODDI) model to represent the GM signal. The feasibility of the proposed approach is shown with numerical simulations and with data from the Human Connectome Project (HCP). The performance of our method is compared to the current state of the art, multi-shell constrained spherical deconvolution (MSCSD). The simulations show that with our new method we can accurately estimate a mixture of two FODs at SNR≥50. With HCP data, the proposed method was able to reconstruct both tangentially and radially oriented FODs in GM, and performed comparably well to MSCSD in computing FODs in WM. When performing fiber tractography, the trajectories reconstructed with mFODs reached the cortex with more spatial continuity and for a longer distance as compared to MSCSD and allowed to reconstruct short trajectories tangential to the cortical folding. In conclusion, we demonstrated that our proposed method allows to perform spherical deconvolution of multiple anisotropic response functions, specifically improving the performances of spherical deconvolution in GM tissue.HighlightsWe introduce a novel framework to perform spherical deconvolution with multiple anisotropic response functions (mFOD)We show that the proposed framework can be used to improve the FOD estimation in the cortical grey matterFiber tractography performed with mFOD reaches the cortical GM with more coverage and contiguity than with previous methodsThe proposed framework is a first step towards GM to GM fiber tractography

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    NeuroImage
    Article . Preprint . 2020 . Peer-reviewed
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    Article . 2020
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    Article . 2020
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    Article . 2020
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      Article . Preprint . 2020 . Peer-reviewed
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      Article . 2020
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    Authors: I, Sibon; A P, Strafella; P, Gravel; J H, Ko; +5 Authors

    High-frequency repetitive transcranial magnetic stimulation (rTMS) of the left dorsolateral prefrontal cortex (LDLPFC) is a technique with purported efficacy as a treatment for major depression. Here, we assessed in vivo, in healthy volunteers, the effect of acute rTMS of the LDLPFC, relative to the stimulation of the left occipital cortex (LOC), on brain regional serotonin synthesis capacity, using the [11C]-alpha-methyl-tryptophan (11C-greek small letter alphaMtrp)/PET method. Ten subjects were studied twice, once following rTMS of the LDLPFC and once following rTMS of the LOC in a randomized counterbalanced order. Three blocks of 15 trains of 10 Hz rTMS were delivered 10 min apart. Behavioural and autonomic measures were recorded before and after each rTMS session. Comparisons of TMS-related changes in regional normalized brain uptake and trapping of 11C-greek small letter alphaMtrp (K*) values were carried out using SPM99. Statistically significant regional differences were identified on the basis of an extent threshold of 50 voxels, with a peak threshold of p = 0.005 uncorrected. Behavioural and autonomic measures were unaffected by rTMS. Relative to LOC stimulation, LDLPFC rTMS was associated with marked changes in normalized K* in limbic areas, with significantly lower values in the left parahippocampal gyrus (BA 28) and the right insula (BA 13), and higher values in the right cingulate gyrus (BA 31) and cuneus (BA 18). These findings indicate that acute rTMS of the LDLPFC in healthy volunteers modulates aspects of tryptophan/5-HT metabolism in limbic areas. Such adaptive changes may contribute to the mechanism of action of prefrontal rTMS in major depression.

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    NeuroImage
    Article . 2007 . Peer-reviewed
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    NeuroImage
    Article . 2006
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      Article . 2007 . Peer-reviewed
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    Authors: Sarah F. Hillenbrand; Richard B. Ivry; John E. Schlerf;

    The blood oxygen level dependent (BOLD) signal, as measured using functional magnetic resonance imaging (fMRI), is widely used as a proxy for changes in neural activity in the brain. Physiological variables such as heart rate (HR) and respiratory variation (RV) affect the BOLD signal in a way that may interfere with the estimation and detection of true task-related neural activity. This interference is of particular concern when these variables themselves show task-related modulations. We first establish that a simple movement task reliably induces a change in HR but not RV. In group data, the effect of HR on the BOLD response was larger and more widespread throughout the brain than were the effects of RV or phase regressors. The inclusion of HR regressors, but not RV or phase regressors, had a small but reliable effect on the estimated hemodynamic response function (HRF) in M1 and the cerebellum. We next asked whether the inclusion of a nested set of physiological regressors combining phase, RV, and HR significantly improved the model fit in individual participants' data sets. There was a significant improvement from HR correction in M1 for the greatest number of participants, followed by RV and phase correction. These improvements were more modest in the cerebellum. These results indicate that accounting for task-related modulation of physiological variables can improve the detection and estimation of true neural effects of interest.

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    NeuroImage
    Article . 2016 . Peer-reviewed
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    NeuroImage
    Article . 2015
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      NeuroImage
      Article . 2015
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    Authors: S. Soloukey; E. Collée; L. Verhoef; D.D. Satoer; +10 Authors

    Accurate, depth-resolved functional imaging is key in both understanding and treatment of the human brain. A new sonography-based imaging technique named functional Ultrasound (fUS) uniquely combines high sensitivity with submillimeter-subsecond spatiotemporal resolution available in large fields-of-view. In this proof-of-concept study we show that: (A) fUS reveals the same eloquent regions as found by fMRI while concomitantly visualizing in-vivo microvascular morphology underlying these functional hemodynamics and (B) fUS-based functional maps are confirmed by Electrocortical Stimulation Mapping (ESM), the current gold-standard in awake neurosurgical practice. This unique cross-modality experiment was performed using motor, visual and language-related functional tasks in patients undergoing awake brain tumor resection. The current work serves as an important milestone towards further maturity of fUS as well as a novel avenue to increase our understanding of hemodynamics-based functional brain imaging.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ NeuroImagearrow_drop_down
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    NeuroImage
    Article . 2023
    Data sources: DOAJ
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    NeuroImage
    Article . 2023
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    NeuroImage
    Article . 2023
    Data sources: KNAW Pure
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    NeuroImage
    Article . 2023 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ NeuroImagearrow_drop_down
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      NeuroImage
      Article . 2023
      Data sources: DOAJ
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      NeuroImage
      Article . 2023
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      NeuroImage
      Article . 2023
      Data sources: KNAW Pure
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      NeuroImage
      Article . 2023 . Peer-reviewed
      License: CC BY
      Data sources: Crossref
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    Authors: Bellomo, A; McGuire, P; Papagni, SA; Mechelli, A; +9 Authors

    Recent studies have identified DAAO as a probable susceptibility gene for schizophrenia and bipolar disorder. However, little is known about how this gene affects brain function to increase vulnerability to these disorders. We examined the impact of DAAO genotype (rs3918346) on brain function in patients with schizophrenia, patients with bipolar I disorder and healthy controls. We tested the hypothesis that a variation in DAAO genotype would be associated with altered prefrontal function and altered functional connectivity in schizophrenia and bipolar disorder. We used functional magnetic resonance imaging to measure brain responses during a verbal fluency task in a total of 121 subjects comprising 40 patients with schizophrenia, 33 patients with bipolar disorder and 48 healthy volunteers. We then used statistical parametric mapping (SPM) and psycho-physiological interaction (PPI) analyses to estimate the main effects of diagnostic group, the main effect of genotype, and their interaction on brain activation and on functional connectivity. Inferences were made at p < 0.05, after correction for multiple comparisons across the whole brain. In the schizophrenia group relative to the control group, patients with one or two copies of the T allele showed lower deactivation in the left precuneus and greater activation in the right posterior cingulate gyrus than patients with two copies of the C allele. This diagnosis × genotype interaction was associated with differences in the functional connectivity of these two regions with other cortical and subcortical areas. In contrast, there were no significant effects of diagnosis or of genotype in comparisons involving bipolar patients. Our results suggest that genetic variation in DAAO has a significant impact on both regional activation and functional connectivity, and provide evidence for a diagnosis-dependent pattern of gene action. © 2011 Elsevier Inc. link_to_subscribed_fulltext

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    NeuroImage
    Article . 2010
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    NeuroImage
    Article . 2011 . Peer-reviewed
    License: Elsevier TDM
    Data sources: Crossref
    HKU Scholars Hub
    Article . 2011
    Data sources: HKU Scholars Hub
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      NeuroImage
      Article . 2010
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      NeuroImage
      Article . 2011 . Peer-reviewed
      License: Elsevier TDM
      Data sources: Crossref
      HKU Scholars Hub
      Article . 2011
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    Authors: van Eijsden, Pieter; Hyder, Fahmeed; Rothman, Douglas L.; Shulman, Robert G.;

    The successes of PET and fMRI in non-invasively localizing sensory functions had encouraged efforts to transform the subjective concepts of cognitive psychology into objective physical measures. The assumption was that mental functions could be decomposed into non-overlapping, context-independent modules that are operated on by separable areas of a computer-like brain. The failures of cognitive modularity and of a very localized phrenology are generally, but not universally, accepted; but in their place, and usually not distinguished from the original revolutionary hopes of clarification, experimental results are being interpreted in terms of rather flexible definitions of both cognitive concepts and the degree of localization. In an alternative approach, we have connected fMRI, (13)C MRS, and electrophysiology measurements of brain energy to connect with observable properties of mental life (i.e., awareness). We illustrate this approach with a sensory stimulation experiment; the degree of localization found in BOLD signals was related to the global energy of the brain which, when manipulated by anesthetics, affected the degree of awareness. The influence of brain energy upon functional imaging maps is changing the interpretations of neuroimaging experiments, from psychological concepts generating computer-like responses to empirical responses dominated by the high brain energy and signaling at rest. In our view "baseline" is an operational term, an adjective that defines a property of a state of the system before it is perturbed by a stimulus. Given the dependence of observable psychological properties upon the "baseline" energy, we believe that it is unnecessarily limiting to de. ne a particular state as the baseline. (C) 2008 Elsevier Inc. All rights reserved.

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    NeuroImage
    Article . 2009
    Data sources: NARCIS
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    Europe PubMed Central
    Other literature type . 2008
    Data sources: PubMed Central
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    NeuroImage
    Article . 2009 . Peer-reviewed
    License: Elsevier TDM
    Data sources: Crossref
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    NeuroImage
    Article
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    NARCIS
    Article . 2009
    Data sources: NARCIS