Nikolaus Weiskopf

University College London, Londinium, England, United Kingdom

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Publications (137)640.79 Total impact

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    Frank Scharnowski, Nikolaus Weiskopf
  • Frontiers in Neuroscience 05/2015; 9. DOI:10.3389/fnins.2015.00168
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    ABSTRACT: Task performance depends on ongoing brain activity which can be influenced by attention, arousal, or motivation. However, such modulating factors of cognitive efficiency are unspecific, can be difficult to control, and are not suitable to facilitate neural processing in a regionally specific manner. Here, we non-pharmacologically manipulated regionally specific brain activity using technically sophisticated real-time fMRI neurofeedback. This was accomplished by training participants to simultaneously control ongoing brain activity in circumscribed motor and memory-related brain areas, namely the supplementary motor area and the parahippocampal cortex. We found that learned voluntary control over these functionally distinct brain areas caused functionally specific behavioral effects, i.e. shortening of motor reaction times and specific interference with memory encoding. The neurofeedback approach goes beyond improving cognitive efficiency by unspecific psychological factors such as attention, arousal, or motivation. It allows for directly manipulating sustained activity of task-relevant brain regions in order to yield specific behavioral or cognitive effects. Copyright © 2015. Published by Elsevier B.V.
    Biological psychology 03/2015; 220. DOI:10.1016/j.biopsycho.2015.03.009 · 3.47 Impact Factor
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    ABSTRACT: We evaluated the performance of an optical camera based prospective motion correction (PMC) system in improving the quality of 3D echo-planar imaging functional MRI data. An optical camera and external marker were used to dynamically track the head movement of subjects during fMRI scanning. PMC was performed by using the motion information to dynamically update the sequence's RF excitation and gradient waveforms such that the field-of-view was realigned to match the subject's head movement. Task-free fMRI experiments on five healthy volunteers followed a 2×2×3 factorial design with the following factors: PMC on or off; 3.0mm or 1.5mm isotropic resolution; and no, slow, or fast head movements. Visual and motor fMRI experiments were additionally performed on one of the volunteers at 1.5mm resolution comparing PMC on vs PMC off for no and slow head movements. Metrics were developed to quantify the amount of motion as it occurred relative to k-space data acquisition. The motion quantification metric collapsed the very rich camera tracking data into one scalar value for each image volume that was strongly predictive of motion-induced artifacts. The PMC system did not introduce extraneous artifacts for the no motion conditions and improved the time series temporal signal-to-noise by 30% to 40% for all combinations of low/high resolution and slow/fast head movement relative to the standard acquisition with no prospective correction. The numbers of activated voxels (p<0.001, uncorrected) in both task-based experiments were comparable for the no motion cases and increased by 78% and 330%, respectively, for PMC on versus PMC off in the slow motion cases. The PMC system is a robust solution to decrease the motion sensitivity of multi-shot 3D EPI sequences and thereby overcoming one of the main roadblocks to their widespread use in fMRI studies. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.
    NeuroImage 03/2015; 16. DOI:10.1016/j.neuroimage.2015.03.013 · 6.13 Impact Factor
  • Brain Stimulation 03/2015; 8(2):426-427. DOI:10.1016/j.brs.2015.01.358 · 5.43 Impact Factor
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    ABSTRACT: Quantitative imaging aims to provide in vivo neuroimaging biomarkers with high research and diagnostic value that are sensitive to underlying tissue microstructure. In order to use these data to examine intra-cortical differences or to define boundaries between different myelo-architectural areas, high resolution data are required. The quality of such measurements is degraded in the presence of motion hindering insight into brain microstructure. Correction schemes are therefore vital for high resolution, whole brain coverage approaches that have long acquisition times and greater sensitivity to motion. Here we evaluate the use of prospective motion correction (PMC) via an optical tracking system to counter intra-scan motion in a high resolution (800 μm isotropic) multi-parameter mapping (MPM) protocol. Data were acquired on six volunteers using a 2 × 2 factorial design permuting the following conditions: PMC on/off and motion/no motion. In the presence of head motion, PMC-based motion correction considerably improved the quality of the maps as reflected by fewer visible artifacts and improved consistency. The precision of the maps, parameterized through the coefficient of variation in cortical sub-regions, showed improvements of 11-25% in the presence of deliberate head motion. Importantly, in the absence of motion the PMC system did not introduce extraneous artifacts into the quantitative maps. The PMC system based on optical tracking offers a robust approach to minimizing motion artifacts in quantitative anatomical imaging without extending scan times. Such a robust motion correction scheme is crucial in order to achieve the ultra-high resolution required of quantitative imaging for cutting edge in vivo histology applications.
    Frontiers in Neuroscience 01/2015; 9:97. DOI:10.3389/fnins.2015.00097
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    ABSTRACT: We present an approach for combining high resolution MRI-based myelin mapping with functional information from electroencephalography (EEG) or magnetoencephalography (MEG). The main contribution to the primary currents detectable with EEG and MEG comes from ionic currents in the apical dendrites of cortical pyramidal cells, aligned perpendicular to the local cortical surface. We provide evidence from an in-vivo experiment that the known microstructural variation in myelinated pyramidal cell density across the cortex predicts the variation of the current density over individuals and thus is of functional relevance. Current dipole moments of pitch onset evoked response fields (ERFs) were source localised by means of a variational Bayesian equivalent current dipole algorithm. The myeloarchitecture was estimated indirectly from individual high resolution quantitative multi-parameter maps (MPMs) acquired at 800μm isotropic resolution. Myelin estimates across cortical areas correlated positively with dipole magnitude. This correlation was spatially specific: regions of interest in auditory cortex provided significantly better models than those covering whole hemispheres. Based on the MPM data we identified the auditory cortical area TE1.2 as the most likely origin of the pitch ERFs measured by MEG. We can now proceed to exploit the higher spatial resolution of quantitative MPMs to identify the cortical origin of M/EEG signals, inform M/EEG source reconstruction and explore structure-function relationships at the fine structural level in the living human brain. Copyright © 2014. Published by Elsevier Inc.
    NeuroImage 12/2014; 108. DOI:10.1016/j.neuroimage.2014.12.030 · 6.13 Impact Factor
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    ABSTRACT: Diffusion Kurtosis Imaging (DKI) is more sensitive to microstructural differences and can be related to more specific micro-scale metrics (e.g. intra-axonal volume fraction) than diffusion tensor imaging (DTI), offering exceptional potential for clinical diagnosis and research into the white and gray matter. Currently DKI is acquired only at low spatial resolution (2-3 mm isotropic), because of the lower signal-to-noise ratio (SNR) and higher artifact level associated with the technically more demanding DKI. Higher spatial resolution of about 1mm is required for the characterization of fine white matter pathways or cortical microstructure. We used restricted-field-of-view imaging in combination with advanced post-processing methods to enable unprecedented high-quality, high-resolution DKI (1.2 mm isotropic) on a clinical 3T scanner. Post-processing was advanced by developing a novel method for Retrospective Eddy current and Motion ArtifacT Correction in High-resolution, multi-shell diffusion data (REMATCH). Furthermore, we applied a powerful edge preserving denoising method, denoted as multi-shell orientation-position-adaptive smoothing (msPOAS). We demonstrated the feasibility of high-quality, high-resolution DKI and its potential for delineating highly myelinated fiber pathways in the motor cortex. REMATCH performs robustly even at the low SNR level of high-resolution DKI, where standard EC and motion correction failed (i.e. produced incorrectly aligned images) and thus biased the diffusion model fit. We showed that the combination of REMATCH and msPOAS increased the contrast between gray and white matter in mean kurtosis (MK) maps by about 35% and at the same time preserves the original distribution of MK values, whereas standard Gaussian smoothing strongly biases the distribution.
    Frontiers in Neuroscience 12/2014; 8(427):1-14. DOI:10.3389/fnins.2014.00427
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    ABSTRACT: Purpose To overcome current limitations in combined transcranial magnetic stimulation (TMS) and functional magnetic resonance imaging (fMRI) studies by employing a dedicated coil array design for 3 Tesla. Methods The state-of-the-art setup for concurrent TMS/fMRI is to use a large birdcage head coil, with the TMS between the subject's head and the MR coil. This setup has drawbacks in sensitivity, positioning, and available imaging techniques. In this study, an ultraslim 7-channel receive-only coil array for 3 T, which can be placed between the subject's head and the TMS, is presented. Interactions between the devices are investigated and the performance of the new setup is evaluated in comparison to the state-of-the-art setup. Results MR sensitivity obtained at the depth of the TMS stimulation is increased by a factor of five. Parallel imaging with an acceleration factor of two is feasible with low g-factors. Possible interactions between TMS and the novel hardware were investigated and were found negligible. Conclusion The novel coil array is safe, strongly improves signal-to-noise ratio in concurrent TMS/fMRI experiments, enables parallel imaging, and allows for flexible positioning of the TMS on the head while ensuring efficient TMS stimulation due to its ultraslim design.
    Magnetic Resonance in Medicine 11/2014; DOI:10.1002/mrm.25535 · 3.40 Impact Factor
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    ABSTRACT: Despite advances in understanding basic organizational principles of the human basal ganglia, accurate in vivo assessment of their anatomical properties is essential to improve early diagnosis in disorders with corticosubcortical pathology and optimize target planning in deep brain stimulation. Main goal of this study was the detailed topological characterization of limbic, associative, and motor subdivisions of the subthalamic nucleus (STN) in relation to corresponding corticosubcortical circuits. To this aim, we used magnetic resonance imaging and investigated independently anatomical connectivity via white matter tracts next to brain tissue properties. On the basis of probabilistic diffusion tractography we identified STN subregions with predominantly motor, associative, and limbic connectivity. We then computed for each of the nonoverlapping STN subregions the covariance between local brain tissue properties and the rest of the brain using high-resolution maps of magnetization transfer (MT) saturation and longitudinal (R1) and transverse relaxation rate (R2*). The demonstrated spatial distribution pattern of covariance between brain tissue properties linked to myelin (R1 and MT) and iron (R2*) content clearly segregates between motor and limbic basal ganglia circuits. We interpret the demonstrated covariance pattern as evidence for shared tissue properties within a functional circuit, which is closely linked to its function. Our findings open new possibilities for investigation of changes in the established covariance pattern aiming at accurate diagnosis of basal ganglia disorders and prediction of treatment outcome. Hum Brain Mapp, 2014. © 2014 Wiley Periodicals, Inc.
    Human Brain Mapping 10/2014; 35(10). DOI:10.1002/hbm.22533 · 6.92 Impact Factor
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    ABSTRACT: Evidence from magnetic resonance imaging (MRI) studies shows that healthy aging is associated with profound changes in cortical and subcortical brain structures. The reliable delineation of cortex and basal ganglia using automated computational anatomy methods based on T1-weighted images remains challenging, which results in controversies in the literature. In this study we use quantitative MRI (qMRI) to gain an insight into the microstructural mechanisms underlying tissue ageing and look for potential interactions between ageing and brain tissue properties to assess their impact on automated tissue classification. To this end we acquired maps of longitudinal relaxation rate R1, effective transverse relaxation rate R2* and magnetization transfer - MT, from healthy subjects (n=96, aged 21 - 88years) using a well-established multi-parameter mapping qMRI protocol. Within the framework of voxel-based quantification we find higher grey matter volume in basal ganglia, cerebellar dentate and prefrontal cortex when tissue classification is based on MT maps compared with T1 maps. These discrepancies between grey matter volume estimates can be attributed to R2* - a surrogate marker of iron concentration, and further modulation by an interaction between R2* and age, both in cortical and subcortical areas. We interpret our findings as direct evidence for the impact of ageing-related brain tissue property changes on automated tissue classification of brain structures using SPM12. Computational anatomy studies of ageing and neurodegeneration should acknowledge these effects, particularly when inferring about underlying pathophysiology from regional cortex and basal ganglia volume changes.
    NeuroImage 09/2014; DOI:10.1016/j.neuroimage.2014.09.044 · 6.13 Impact Factor
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    ABSTRACT: Relaxation rates provide important information about tissue microstructure. Multi-parameter mapping (MPM) estimates multiple relaxation parameters from multi-echo FLASH acquisitions with different basic contrasts, i.e., proton density (PD), T1 or magnetization transfer (MT) weighting. Motion can particularly affect maps of the apparent transverse relaxation rate R2(*), which are derived from the signal of PD-weighted images acquired at different echo times. To address the motion artifacts, we introduce ESTATICS, which robustly estimates R2(*) from images even when acquired with different basic contrasts. ESTATICS extends the fitted signal model to account for inherent contrast differences in the PDw, T1w and MTw images. The fit was implemented as a conventional ordinary least squares optimization and as a robust fit with a small or large confidence interval. These three different implementations of ESTATICS were tested on data affected by severe motion artifacts and data with no prominent motion artifacts as determined by visual assessment or fast optical motion tracking. ESTATICS improved the quality of the R2(*) maps and reduced the coefficient of variation for both types of data-with average reductions of 30% when severe motion artifacts were present. ESTATICS can be applied to any protocol comprised of multiple 2D/3D multi-echo FLASH acquisitions as used in the general research and clinical setting.
    Frontiers in Neuroscience 09/2014; 8:278. DOI:10.3389/fnins.2014.00278
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    ABSTRACT: The lateral habenula (LHb) has been shown to respond to cues that predict aversive stimuli in non-human primates (Matsumoto & Hikosaka, 2009, Nat Neurosci, 12 (1), 77-84) and has been implicated in reinforcement processing and the pathophysiology of major depression (MDD) (Roiser et al, Biol Psychiatry, 66 (5), 441-450), possibly via reciprocal connections with monoaminergic nuclei. We report the first high-resolution fMRI investigation of haemodynamic responses during appetitive and aversive conditioning in the LHb in unipolar MDD. Additionally, we report the first assessment of tonic habenula function using quantitative Arterial Spin Labelling (ASL) in MDD.
    Journal of Neurology Neurosurgery & Psychiatry 08/2014; 85(8):e3. DOI:10.1136/jnnp-2014-308883.31 · 5.58 Impact Factor
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    ABSTRACT: Learning what to approach, and what to avoid, involves assigning value to environmental cues that predict positive and negative events. Studies in animals indicate that the lateral habenula encodes the previously learned negative motivational value of stimuli. However, involvement of the habenula in dynamic trial-by-trial aversive learning has not been assessed, and the functional role of this structure in humans remains poorly characterized, in part, due to its small size. Using high-resolution functional neuroimaging and computational modeling of reinforcement learning, we demonstrate positive habenula responses to the dynamically changing values of cues signaling painful electric shocks, which predict behavioral suppression of responses to those cues across individuals. By contrast, negative habenula responses to monetary reward cue values predict behavioral invigoration. Our findings show that the habenula plays a key role in an online aversive learning system and in generating associated motivated behavior in humans.
    Proceedings of the National Academy of Sciences 07/2014; 111(32). DOI:10.1073/pnas.1323586111 · 9.81 Impact Factor
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    ABSTRACT: We present a novel multi-shell position orientation adaptive smoothing (msPOAS) method for diffusion-weighted magnetic resonance data. Smoothing in voxel and diffusion gradient space is embedded in an iterative adaptive multiscale approach. The adaptive character avoids blurring of the inherent structures and preserves discontinuities. The simultaneous treatment of all q-shells improves the stability compared to single shell approaches such as the original POAS method. The msPOAS implementation simplifies and speeds up calculations, compared to POAS, facilitating its practical application. Simulations and heuristics support the face validity of the technique and its rigorousness. The characteristics of msPOAS were evaluated on single and multi-shell diffusion data of the human brain. Significant reduction in noise while preserving the fine structure was demonstrated for diffusion weighted images, standard DTI analysis and advanced diffusion models such as NODDI. MsPOAS effectively improves the poor signal-to-noise ratio in highly diffusion weighted multi-shell diffusion data, which is required by recent advanced diffusion micro-structure models. We demonstrate the superiority of the new method compared to other advanced denoising methods.
    NeuroImage 07/2014; 95:90-105. DOI:10.1016/j.neuroimage.2014.03.053 · 6.13 Impact Factor
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    ABSTRACT: Background / Purpose: Functional and diffusion-weighted MRI are usually performed using echo-planar imaging (EPI). A major problem with EPI are geometric distortions caused by magnetic field inhomogeneities, especially at high field strength. To determine the best way to deal with these, we compared three methods for EPI distortion correction. Main conclusion: Overall, the methods based on opposite phase encoding directions consistently outperform the fieldmap-based method.
    20th Annual Meeting of the Organization for Human Brain Mapping (OHBM) 2014; 07/2014
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    Annual Meeting of the Organization for Human Brain Mapping, Hamburg, Germany; 06/2014
  • Annual Meeting of the Organization for Human Brain Mapping, Hamburg, Germany; 06/2014
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    ABSTRACT: We present an implementation of a recently developed noise reduction algorithm for dMRI data, called multi-shell position orientation adaptive smoothing (msPOAS), as a toolbox for SPM. The method intrinsically adapts to the structures of different size and shape in dMRI and hence avoids blurring typically observed in non-adaptive smoothing. We give examples for the usage of the toolbox and explain the determination of experiment-dependent parameters for an optimal performance of msPOAS.
    Neuroinformatics 04/2014; DOI:10.1007/s12021-014-9228-3 · 3.10 Impact Factor
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    ABSTRACT: PurposeThe longitudinal relaxation rate (R1) measured in vivo depends on the local microstructural properties of the tissue, such as macromolecular, iron, and water content. Here, we use whole brain multiparametric in vivo data and a general linear relaxometry model to describe the dependence of R1 on these components. We explore a) the validity of having a single fixed set of model coefficients for the whole brain and b) the stability of the model coefficients in a large cohort.Methods Maps of magnetization transfer (MT) and effective transverse relaxation rate (R2*) were used as surrogates for macromolecular and iron content, respectively. Spatial variations in these parameters reflected variations in underlying tissue microstructure. A linear model was applied to the whole brain, including gray/white matter and deep brain structures, to determine the global model coefficients. Synthetic R1 values were then calculated using these coefficients and compared with the measured R1 maps.ResultsThe model's validity was demonstrated by correspondence between the synthetic and measured R1 values and by high stability of the model coefficients across a large cohort.ConclusionA single set of global coefficients can be used to relate R1, MT, and R2* across the whole brain. Our population study demonstrates the robustness and stability of the model. Magn Reson Med, 2014. © 2014 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc.
    Magnetic Resonance in Medicine 04/2014; 73(3). DOI:10.1002/mrm.25210 · 3.40 Impact Factor

Publication Stats

5k Citations
640.79 Total Impact Points

Institutions

  • 2004–2015
    • University College London
      • • Wellcome Trust Centre for Neuroimaging
      • • Institute of Neurology
      • • Wellcome Department of Imaging Neuroscience
      Londinium, England, United Kingdom
  • 2014
    • Wellcome Trust
      Londinium, England, United Kingdom
  • 2010–2014
    • UCL Eastman Dental Institute
      Londinium, England, United Kingdom
  • 2011
    • Institut Philippe-Pinel de Montréal
      Montréal, Quebec, Canada
  • 2002–2009
    • University of Tuebingen
      • • Institute of Medical Psychology and Behavioral Neurobiology
      • • Department of Neurology
      Tübingen, Baden-Württemberg, Germany
  • 2006
    • University of Oxford
      Oxford, England, United Kingdom