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See detailThe heterogeneity of the left dorsal premotor cortex evidenced by multimodal connectivity-based parcellation and functional characterization
Genon, Sarah ULiege; Reid, Andrew; Li, Hai et al

in NeuroImage (in press)

Despite the common conception of the dorsal premotor cortex (PMd) as a single brain region, its diverse connectivity profiles and behavioral heterogeneity argue for a differentiated organization of the ... [more ▼]

Despite the common conception of the dorsal premotor cortex (PMd) as a single brain region, its diverse connectivity profiles and behavioral heterogeneity argue for a differentiated organization of the PMd. A previous study revealed that the right PMd is characterized by a rostro-caudal and a ventro-dorsal distinction dividing it into five subregions: rostral, central, caudal, ventral and dorsal. The present study assessed whether a similar organization is present in the left hemisphere, by capitalizing on a multimodal data-driven approach combining connectivity-based parcellation (CBP) based on meta-analytic modeling, resting- state functional connectivity, and probabilistic diffusion tractography. The resulting PMd modules were then characterized based on multimodal functional connectivity and a quantitative analysis of associated behavioral functions. Analyzing the clusters consistent across all modalities revealed an organization of the left PMd that mirrored its right counterpart to a large degree. Again, caudal, central and rostral modules reflected a cognitive- motor gradient and a premotor eye-field was found in the ventral part of the left PMd. In addition, a distinct module linked to abstract cognitive functions was observed in the rostro- ventral left PMd across all CBP modalities, implying greater differentiation of higher cognitive functions for the left than the right PMd. [less ▲]

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See detailSearching for behavior relating to grey matter volume in a-priori defined right dorsal premotor regions: lessons learned.
Genon, Sarah ULiege; Wensing, Tobias; Reid, Andrew et al

in NeuroImage (2017)

Recently, we showed that the functional heterogeneity of the right dorsal premotor (PMd) cortex could be better understood by dividing it into five subregions that showed different behavioral associations ... [more ▼]

Recently, we showed that the functional heterogeneity of the right dorsal premotor (PMd) cortex could be better understood by dividing it into five subregions that showed different behavioral associations according to task-based activations studies. The present study investigated whether the revealed behavioral profile could be corroborated and complemented by a structural brain behavior correlation approach in two healthy adults cohorts. Grey matter volume within the five volumes of interest (VOI-GM) was computed using voxel-based morphometry. Associations between the inter-individual differences in VOI-GM and performance across a range of neuropsychological tests were assessed in the two cohorts with and without correction for demographical variables. Additional analyses were performed in random smaller subsamples drawn from each of the two cohorts. In both cohorts, correlation coefficients were low; only few were significant and a considerable number of correlations were counterintuitive in their directions (i.e., higher performance related to lower GMV). Furthermore, correlation patterns were inconsistent between the two cohorts. Subsampling revealed that correlation patterns could vary widely across small samples and that negative correlations were as likely as positive correlations. Thus, the structural brain/behavior approach did not corroborate the functional profiles of the PMd subregions inferred from activation studies, suggesting that local recruitment by fMRI studies does not necessarily imply covariance of local structure with behavioral performance in healthy adults. We discuss the limitations of such studies and related recommendations for future studies. [less ▲]

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See detailAltered functional brain connectivity in patients with visually induced dizziness
Van Ombergen, Angelique; Heine, Lizette ULiege; Jillings, Steven et al

in NeuroImage (2017), 14

Background: Vestibular patients occasionally report aggravation or triggering of their symptoms by visual stimuli, which is called visually induced dizziness (VID). These patients therefore experience ... [more ▼]

Background: Vestibular patients occasionally report aggravation or triggering of their symptoms by visual stimuli, which is called visually induced dizziness (VID). These patients therefore experience dizziness, discomfort, disorientation and postural unsteadiness. The underlying pathophysiology of VID is still poorly understood. Objective: The aimof the current explorative study was to gain a first insight in the underlying neural aspects of VID. Methods:We included 10 VID patients and 10 healthymatched controls, all ofwhich underwent a resting state fMRI scan session. Changes in functional connectivitywere explored bymeans of the intrinsic connectivity contrast (ICC). Seed-based analysis was subsequently performed in visual and vestibular seeds. Results: We found a decreased functional connectivity in the right central operculum (superior temporal gyrus), as well as increased functional connectivity in the occipital pole in VID patients as compared to controls in a hypothesis-free analysis. A weaker functional connectivity between the thalamus and most of the right putamen was measured in VID patients in comparison to controls in a seed-based analysis. Furthermore, also by means of a seed-based analysis, a decreased functional connectivity between the visual associative area and the left parahippocampal gyrus was found in VID patients. Additionally,we found increased functional connectivity between thalamus and occipital and cerebellar areas in the VID patients, as well as between the associative visual cortex and both middle frontal gyrus and precuneus. Conclusions:We found alterations in the visual and vestibular cortical network in VID patients that could underlie the typical VID symptoms such as a worsening of their vestibular symptoms when being exposed to challenging visual stimuli. These preliminary findings provide the first insights into the underlying functional brain connectivity in VID patients. Future studies should extend these findings by employing larger sample sizes, by investigating specific task-based paradigms in these patients and by exploring the implications for treatment. [less ▲]

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See detailExploring sex differences in the adult zebra finch brain: in vivo diffusion tensor imaging and ex vivo super-resolution track density imaging
Hamaide, J.; De Groof, G.; Van Steenkiste, G. et al

in NeuroImage (2017), 146

Zebra finches are an excellent model to study the process of vocal learning, a complex socially-learned tool of communication that forms the basis of spoken human language. So far, structural ... [more ▼]

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

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See detailInvestigating resting-state functional connectivity in the cervical spinal cord at 3T.
Eippert, Falk; Kong, Yazhuo; Winkler, Anderson ULiege et al

in NeuroImage (2017), 147

The study of spontaneous fluctuations in the blood-oxygen-level-dependent (BOLD) signal has recently been extended from the brain to the spinal cord. Two ultra-high field functional magnetic resonance ... [more ▼]

The study of spontaneous fluctuations in the blood-oxygen-level-dependent (BOLD) signal has recently been extended from the brain to the spinal cord. Two ultra-high field functional magnetic resonance imaging (fMRI) studies in humans have provided evidence for reproducible resting-state connectivity between the dorsal horns as well as between the ventral horns, and a study in non-human primates has shown that these resting-state signals are impacted by spinal cord injury. As these studies were carried out at ultra-high field strengths using region-of-interest (ROI) based analyses, we investigated whether such resting-state signals could also be observed at the clinically more prevalent field strength of 3T. In a reanalysis of a sample of 20 healthy human participants who underwent a resting-state fMRI acquisition of the cervical spinal cord, we were able to observe significant dorsal horn connectivity as well as ventral horn connectivity, but no consistent effects for connectivity between dorsal and ventral horns, thus replicating the human 7T results. These effects were not only observable when averaging along the acquired length of the spinal cord, but also when we examined each of the acquired spinal segments separately, which showed similar patterns of connectivity. Finally, we investigated the robustness of these resting-state signals against variations in the analysis pipeline by varying the type of ROI creation, temporal filtering, nuisance regression and connectivity metric. We observed that - apart from the effects of band-pass filtering - ventral horn connectivity showed excellent robustness, whereas dorsal horn connectivity showed moderate robustness. Together, our results provide evidence that spinal cord resting-state connectivity is a robust and spatially consistent phenomenon that could be a valuable tool for investigating the effects of pathology, disease progression, and treatment response in neurological conditions with a spinal component, such as spinal cord injury. [less ▲]

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See detailMapping the functional connectome traits of levels of consciousness
Amico, Enrico; Marinazzo, Daniele; Di Perri, Carol ULiege et al

in NeuroImage (2017)

Examining task-free functional connectivity (FC) in the human brain offers insights on how spontaneous integration and segregation of information relate to human cognition, and how this organization may ... [more ▼]

Examining task-free functional connectivity (FC) in the human brain offers insights on how spontaneous integration and segregation of information relate to human cognition, and how this organization may be altered in different conditions, and neurological disorders. This is particularly relevant for patients in disorders of consciousness (DOC) following severe acquired brain damage and coma, one of the most devastating conditions in modern medical care. We present a novel data-driven methodology, connICA, which implements Independent Component Analysis (ICA) for the extraction of robust independent FC patterns (FC-traits) from a set of individual functional connectomes, without imposing any a priori data stratification into groups. We here apply connICA to investigate associations between network-traits derived from task-free FC and cognitive features that define levels of consciousness. Three main independent FC-traits were identified and linked to consciousness-related clinical features. The first one represents the functional configuration of an "awake resting" brain, and is associated to the level of arousal. The second FC-trait reflects the disconnection of the visual and sensory-motor connectivity patterns and relates to the ability of communicating with the external environment. The third FC-trait isolates the connectivity pattern encompassing the fronto-parietal and the default-mode network areas as well as the interaction between left and right hemisphere, which are also associated to the awareness of the self and its surroundings. Each FC-trait represents a distinct functional process with a role in the degradation of conscious states in functional brain networks, shedding further light on the functional subcircuits that get disrupted in severe brain-damage. [less ▲]

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See detailANIMA: A data-sharing initiative for neuroimaging meta-analyses
Reid, Andrew T.; Bzdok, Danilo; Genon, Sarah ULiege et al

in NeuroImage (2016), 124(B), 1245-1253

Meta-analytic techniques allow cognitive neuroscientists to pool large amounts of data across many individual task-based functional neuroimaging experiments. These methods have been aided by the ... [more ▼]

Meta-analytic techniques allow cognitive neuroscientists to pool large amounts of data across many individual task-based functional neuroimaging experiments. These methods have been aided by the introduction of online databases such as Brainmap.org or Neurosynth.org, which collate peak activation coordinates obtained from thousands of published studies. Findings from meta-analytic studies typically include brain regions which are consistently activated across studies for specific contrasts, investigating cognitive or clinical hypotheses. These regions can be subsequently used as the basis for seed-based connectivity analysis, or formally compared to neuroimaging data in order to help interpret new findings. To facilitate such approaches, we have developed a new online repository of meta-analytic neuroimaging results, named the Archive of Neuroimaging Meta-analyses (ANIMA). The ANIMA platform consists of an intuitive online interface for querying, downloading, and contributing data from published meta-analytic studies. Additionally, to aid the process of organizing, visualizing, and working with these data, we present an open-source desktop application called Volume Viewer. Volume Viewer allows users to easily arrange imaging data into composite stacks, and save these sessions as individual files, which can also be uploaded to the ANIMA database. The application also allows users to perform basic functions, such as computing conjunctions between images, or extracting regions-of-interest or peak coordinates for further analysis. The introduction of this new resource will enhance the ability of researchers to both share their findings and incorporate existing meta-analytic results into their own research. [less ▲]

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See detailThe common genetic influence over processing speed and white matter microstructure: Evidence from the Old Order Amish and Human Connectome Projects.
Kochunov, Peter; Thompson, Paul M.; Winkler, Anderson ULiege et al

in NeuroImage (2016), 125

Speed with which brain performs information processing influences overall cognition and is dependent on the white matter fibers. To understand genetic influences on processing speed and white matter FA ... [more ▼]

Speed with which brain performs information processing influences overall cognition and is dependent on the white matter fibers. To understand genetic influences on processing speed and white matter FA, we assessed processing speed and diffusion imaging fractional anisotropy (FA) in related individuals from two populations. Discovery analyses were performed in 146 individuals from large Old Order Amish (OOA) families and findings were replicated in 485 twins and siblings of the Human Connectome Project (HCP). The heritability of processing speed was h(2)=43% and 49% (both p<0.005), while the heritability of whole brain FA was h(2)=87% and 88% (both p<0.001), in the OOA and HCP, respectively. Whole brain FA was significantly correlated with processing speed in the two cohorts. Quantitative genetic analysis demonstrated a significant degree to which common genes influenced joint variation in FA and brain processing speed. These estimates suggested common sets of genes influencing variation in both phenotypes, consistent with the idea that common genetic variations contributing to white matter may also support their associated cognitive behavior. [less ▲]

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See detailFaster permutation inference in brain imaging.
Winkler, Anderson ULiege; Ridgway, Gerard R.; Douaud, Gwenaelle et al

in NeuroImage (2016), 141

Permutation tests are increasingly being used as a reliable method for inference in neuroimaging analysis. However, they are computationally intensive. For small, non-imaging datasets, recomputing a model ... [more ▼]

Permutation tests are increasingly being used as a reliable method for inference in neuroimaging analysis. However, they are computationally intensive. For small, non-imaging datasets, recomputing a model thousands of times is seldom a problem, but for large, complex models this can be prohibitively slow, even with the availability of inexpensive computing power. Here we exploit properties of statistics used with the general linear model (GLM) and their distributions to obtain accelerations irrespective of generic software or hardware improvements. We compare the following approaches: (i) performing a small number of permutations; (ii) estimating the p-value as a parameter of a negative binomial distribution; (iii) fitting a generalised Pareto distribution to the tail of the permutation distribution; (iv) computing p-values based on the expected moments of the permutation distribution, approximated from a gamma distribution; (v) direct fitting of a gamma distribution to the empirical permutation distribution; and (vi) permuting a reduced number of voxels, with completion of the remainder using low rank matrix theory. Using synthetic data we assessed the different methods in terms of their error rates, power, agreement with a reference result, and the risk of taking a different decision regarding the rejection of the null hypotheses (known as the resampling risk). We also conducted a re-analysis of a voxel-based morphometry study as a real-data example. All methods yielded exact error rates. Likewise, power was similar across methods. Resampling risk was higher for methods (i), (iii) and (v). For comparable resampling risks, the method in which no permutations are done (iv) was the absolute fastest. All methods produced visually similar maps for the real data, with stronger effects being detected in the family-wise error rate corrected maps by (iii) and (v), and generally similar to the results seen in the reference set. Overall, for uncorrected p-values, method (iv) was found the best as long as symmetric errors can be assumed. In all other settings, including for familywise error corrected p-values, we recommend the tail approximation (iii). The methods considered are freely available in the tool PALM - Permutation Analysis of Linear Models. [less ▲]

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See detailNeural correlates of event clusters in past and future thoughts: How the brain integrates specific episodes with autobiographical knowledge
Demblon, Julie ULiege; Bahri, Mohamed Ali ULiege; D'Argembeau, Arnaud ULiege

in NeuroImage (2016), 127

When remembering the past or envisioning the future, events often come to mind in organized sequences or stories rather than in isolation from one another. The aim of the present fMRI study was to ... [more ▼]

When remembering the past or envisioning the future, events often come to mind in organized sequences or stories rather than in isolation from one another. The aim of the present fMRI study was to investigate the neural correlates of such event clusters. Participants were asked to consider pairs of specific past or future events: in one condition, the two events were part of the same event cluster (i.e., they were thematically and/or causally related to each other), whereas in another condition the two events only shared a surface feature (i.e., their location); a third condition was also included, in which the two events were unrelated to each other. The results showed that the processing of past and future events that were part of a same cluster was associated with higher activation in the medial prefrontal cortex (PFC), rostrolateral PFC, and left lateral temporal and parietal regions, compared to the two other conditions. Furthermore, functional connectivity analyses revealed an increased coupling between these cortical regions. These findings suggest that largely similar processes are involved in organizing events in clusters for the past and the future. The medial and rostrolateral PFC might play a pivotal role in mediating the integration of specific events with conceptual autobiographical knowledge ‘stored’ in more posterior regions. Through this integrative process, this set of brain regions might contribute to the attribution of an overarching meaning to representations of specific past and future events, by contextualizing them with respect to personal goals and general knowledge about one's life story. [less ▲]

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See detailNeuronal excitation/inhibition balance is set by the need for sleep and the biological clock
Phillips, Christophe ULiege; Chellappa, Sarah Laxhmi ULiege; Ly, Julien et al

in NeuroImage (2015, June)

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See detailHeritability of fractional anisotropy in human white matter: a comparison of Human Connectome Project and ENIGMA-DTI data.
Kochunov, Peter; Jahanshad, Neda; Marcus, Daniel et al

in NeuroImage (2015), 111

The degree to which genetic factors influence brain connectivity is beginning to be understood. Large-scale efforts are underway to map the profile of genetic effects in various brain regions. The NIH ... [more ▼]

The degree to which genetic factors influence brain connectivity is beginning to be understood. Large-scale efforts are underway to map the profile of genetic effects in various brain regions. The NIH-funded Human Connectome Project (HCP) is providing data valuable for analyzing the degree of genetic influence underlying brain connectivity revealed by state-of-the-art neuroimaging methods. We calculated the heritability of the fractional anisotropy (FA) measure derived from diffusion tensor imaging (DTI) reconstruction in 481 HCP subjects (194/287 M/F) consisting of 57/60 pairs of mono- and dizygotic twins, and 246 siblings. FA measurements were derived using (Enhancing NeuroImaging Genetics through Meta-Analysis) ENIGMA DTI protocols and heritability estimates were calculated using the SOLAR-Eclipse imaging genetic analysis package. We compared heritability estimates derived from HCP data to those publicly available through the ENIGMA-DTI consortium, which were pooled together from five-family based studies across the US, Europe, and Australia. FA measurements from the HCP cohort for eleven major white matter tracts were highly heritable (h(2)=0.53-0.90, p<10(-5)), and were significantly correlated with the joint-analytical estimates from the ENIGMA cohort on the tract and voxel-wise levels. The similarity in regional heritability suggests that the additive genetic contribution to white matter microstructure is consistent across populations and imaging acquisition parameters. It also suggests that the overarching genetic influence provides an opportunity to define a common genetic search space for future gene-discovery studies. Uniquely, the measurements of additive genetic contribution performed in this study can be repeated using online genetic analysis tools provided by the HCP ConnectomeDB web application. [less ▲]

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See detailFast and powerful heritability inference for family-based neuroimaging studies.
Ganjgahi, Habib; Winkler, Anderson ULiege; Glahn, David C. et al

in NeuroImage (2015), 115

Heritability estimation has become an important tool for imaging genetics studies. The large number of voxel- and vertex-wise measurements in imaging genetics studies presents a challenge both in terms of ... [more ▼]

Heritability estimation has become an important tool for imaging genetics studies. The large number of voxel- and vertex-wise measurements in imaging genetics studies presents a challenge both in terms of computational intensity and the need to account for elevated false positive risk because of the multiple testing problem. There is a gap in existing tools, as standard neuroimaging software cannot estimate heritability, and yet standard quantitative genetics tools cannot provide essential neuroimaging inferences, like family-wise error corrected voxel-wise or cluster-wise P-values. Moreover, available heritability tools rely on P-values that can be inaccurate with usual parametric inference methods. In this work we develop fast estimation and inference procedures for voxel-wise heritability, drawing on recent methodological results that simplify heritability likelihood computations (Blangero et al., 2013). We review the family of score and Wald tests and propose novel inference methods based on explained sum of squares of an auxiliary linear model. To address problems with inaccuracies with the standard results used to find P-values, we propose four different permutation schemes to allow semi-parametric inference (parametric likelihood-based estimation, non-parametric sampling distribution). In total, we evaluate 5 different significance tests for heritability, with either asymptotic parametric or permutation-based P-value computations. We identify a number of tests that are both computationally efficient and powerful, making them ideal candidates for heritability studies in the massive data setting. We illustrate our method on fractional anisotropy measures in 859 subjects from the Genetics of Brain Structure study. [less ▲]

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See detailMulti-level block permutation.
Winkler, Anderson ULiege; Webster, Matthew A.; Vidaurre, Diego et al

in NeuroImage (2015), 123

Under weak and reasonable assumptions, mainly that data are exchangeable under the null hypothesis, permutation tests can provide exact control of false positives and allow the use of various non-standard ... [more ▼]

Under weak and reasonable assumptions, mainly that data are exchangeable under the null hypothesis, permutation tests can provide exact control of false positives and allow the use of various non-standard statistics. There are, however, various common examples in which global exchangeability can be violated, including paired tests, tests that involve repeated measurements, tests in which subjects are relatives (members of pedigrees) - any dataset with known dependence among observations. In these cases, some permutations, if performed, would create data that would not possess the original dependence structure, and thus, should not be used to construct the reference (null) distribution. To allow permutation inference in such cases, we test the null hypothesis using only a subset of all otherwise possible permutations, i.e., using only the rearrangements of the data that respect exchangeability, thus retaining the original joint distribution unaltered. In a previous study, we defined exchangeability for blocks of data, as opposed to each datum individually, then allowing permutations to happen within block, or the blocks as a whole to be permuted. Here we extend that notion to allow blocks to be nested, in a hierarchical, multi-level definition. We do not explicitly model the degree of dependence between observations, only the lack of independence; the dependence is implicitly accounted for by the hierarchy and by the permutation scheme. The strategy is compatible with heteroscedasticity and variance groups, and can be used with permutations, sign flippings, or both combined. We evaluate the method for various dependence structures, apply it to real data from the Human Connectome Project (HCP) as an example application, show that false positives can be avoided in such cases, and provide a software implementation of the proposed approach. [less ▲]

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See detailA finite-element reciprocity solution for EEG forward modeling with realistic individual head models
Ziegler, Erik ULiege; Chellappa, Sarah Laxhmi ULiege; Gaggioni, Giulia ULiege et al

in NeuroImage (2014), 103

Highlights • Creates EEG forward models suitable for high-resolution source localization. • Automatic T1-based whole-head finite element meshing and leadfield computation. • Pipelines can incorporate ... [more ▼]

Highlights • Creates EEG forward models suitable for high-resolution source localization. • Automatic T1-based whole-head finite element meshing and leadfield computation. • Pipelines can incorporate conductivity tensors from diffusion-weighted images. • Open-source toolbox shared under a permissive software license. • Accuracy comparable to SimBio FEM and superior to OpenMEEG BEM solutions. [less ▲]

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See detailMapping track density changes in nigrostriatal and extranigral pathways in Parkinson's disease
Ziegler, Erik ULiege; Rouillard, Maud; André, Elodie et al

in NeuroImage (2014), 99

Highlights First whole-brain probabilistic tractography study in Parkinson's disease High quality diffusion-weighted images (120 gradient directions, b = 2500 s/mm2) Voxel-based group analysis comparing ... [more ▼]

Highlights First whole-brain probabilistic tractography study in Parkinson's disease High quality diffusion-weighted images (120 gradient directions, b = 2500 s/mm2) Voxel-based group analysis comparing early-stage patients and controls Abnormal reconstructed track density in the nigrostriatal pathway and brainstem Track density also increased in limbic and cognitive circuits. [less ▲]

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See detailPermutation inference for the general linear model.
Winkler, Anderson ULiege; Ridgway, Gerard R.; Webster, Matthew A. et al

in NeuroImage (2014), 92

Permutation methods can provide exact control of false positives and allow the use of non-standard statistics, making only weak assumptions about the data. With the availability of fast and inexpensive ... [more ▼]

Permutation methods can provide exact control of false positives and allow the use of non-standard statistics, making only weak assumptions about the data. With the availability of fast and inexpensive computing, their main limitation would be some lack of flexibility to work with arbitrary experimental designs. In this paper we report on results on approximate permutation methods that are more flexible with respect to the experimental design and nuisance variables, and conduct detailed simulations to identify the best method for settings that are typical for imaging research scenarios. We present a generic framework for permutation inference for complex general linear models (GLMS) when the errors are exchangeable and/or have a symmetric distribution, and show that, even in the presence of nuisance effects, these permutation inferences are powerful while providing excellent control of false positives in a wide range of common and relevant imaging research scenarios. We also demonstrate how the inference on GLM parameters, originally intended for independent data, can be used in certain special but useful cases in which independence is violated. Detailed examples of common neuroimaging applications are provided, as well as a complete algorithm - the "randomise" algorithm - for permutation inference with the GLM. [less ▲]

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See detailSpatiotemporal properties of auditory intensity processing in multisensor MEG.
Wyss, C.; Boers, F.; Kawohl, W. et al

in NeuroImage (2014), 102 Pt 2

Loudness dependence of auditory evoked potentials (LDAEP) evaluates loudness processing in the human auditory system and is often altered in patients with psychiatric disorders. Previous research has ... [more ▼]

Loudness dependence of auditory evoked potentials (LDAEP) evaluates loudness processing in the human auditory system and is often altered in patients with psychiatric disorders. Previous research has suggested that this measure may be used as an indicator of the central serotonergic system through the highly serotonergic innervation of the auditory cortex. However, differences among the commonly used analysis approaches (such as source analysis and single electrode estimation) may lead to different results. Putatively due to discrepancies of the underlying structures being measured. Therefore, it is important to learn more about how and where in the brain loudness variation is processed. We conducted a detailed investigation of the LDAEP generators and their temporal dynamics by means of multichannel magnetoencephalography (MEG). Evoked responses to brief tones of five different intensities were recorded from 19 healthy participants. We used magnetic field tomography in order to appropriately localize superficial as well as deep source generators of which we conducted a time series analysis. The results showed that apart from the auditory cortex other cortical sources exhibited activation during the N1/P2 time window. Analysis of time courses in the regions of interest revealed a sequential cortical activation from primary sensory areas, particularly the auditory and somatosensory cortex to posterior cingulate cortex (PCC) and to premotor cortex (PMC). The additional activation within the PCC and PMC has implications on the analysis approaches used in LDAEP research. [less ▲]

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See detailSimultaneous EEG-fMRI acquisition at low, high and ultra-high magnetic fields up to 9.4 T: perspectives and challenges.
Neuner, Irene; Arrubla Martinez, Jorge Andres ULiege; Felder, Jorg et al

in NeuroImage (2014), 102 Pt 1

In this perspectives article we highlight the advantages of simultaneous acquisition of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). As MRI moves towards using ultra-high ... [more ▼]

In this perspectives article we highlight the advantages of simultaneous acquisition of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). As MRI moves towards using ultra-high magnetic fields in the quest for increased signal-to-noise, the question arises whether combined EEG-fMRI measurements are feasible at magnetic fields of 7 T and higher. We describe the challenges of MRI-EEG at 1.5, 3, 7 and 9.4 T and review the proposed solutions. In an outlook, we discuss further developments such as simultaneous trimodal imaging using MR, positron emission tomography (PET) and EEG under the same physiological conditions in the same subject. [less ▲]

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See detailSleep sharpens sensory stimulus coding in human visual cortex after fear conditioning.
Sterpenich, Virginie; Piguet, Camille; Desseilles, Martin ULiege et al

in NeuroImage (2014), 100

Efficient perceptual identification of emotionally-relevant stimuli requires optimized neural coding. Because sleep contributes to neural plasticity mechanisms, we asked whether the perceptual ... [more ▼]

Efficient perceptual identification of emotionally-relevant stimuli requires optimized neural coding. Because sleep contributes to neural plasticity mechanisms, we asked whether the perceptual representation of emotionally-relevant stimuli within sensory cortices is modified after a period of sleep. We show combined effects of sleep and aversive conditioning on subsequent discrimination of face identity information, with parallel plasticity in the amygdala and visual cortex. After one night of sleep (but neither immediately nor after an equal waking interval), a fear-conditioned face was better detected when morphed with another identity. This behavioral change was accompanied by increased selectivity of the amygdala and face-responsive fusiform regions. Overnight neural changes can thus sharpen the representation of threat-related stimuli in cortical sensory areas, in order to improve detection in impoverished or ambiguous situations. These findings reveal an important role of sleep in shaping cortical selectivity to emotionally-relevant cues and thus promoting adaptive responses to new dangers. [less ▲]

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