Danish Research Center for Magnetic Resonance

Magnetic, Denmark

Danish Research Center for Magnetic Resonance

Magnetic, Denmark
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Pellegrino G.,Biomedical University of Rome | Pellegrino G.,Fondazione Alberto Sordi Research Institute for Ageing | Pellegrino G.,Montreal Neurological Institute | Tombini M.,Biomedical University of Rome | And 11 more authors.
Clinical EEG and Neuroscience | Year: 2017

Introduction. We aimed to test differences between healthy subjects and patients with respect to slow wave activity during wakefulness and sleep. Methods. Fifteen patients affected by nonlesional focal epilepsy originating within temporal areas and fourteen matched controls underwent a 24-hour EEG recording. We studied the EEG power spectral density during wakefulness and sleep in delta (1-4 Hz), theta (5-7 Hz), alpha (8-11 Hz), sigma (12-15 Hz), and beta (16-20 Hz) bands. Results. During sleep, patients with focal epilepsy showed higher power from delta to beta frequency bands compared with controls. The effect was widespread for alpha band and above, while localized over the affected hemisphere for delta (sleep cycle 1, P =.006; sleep cycle 2, P =.008; sleep cycle 3, P =.017). The analysis of interhemispheric differences showed that the only frequency band stronger over the affected regions was the delta band during the first 2 sleep cycles (sleep cycle 1, P =.014; sleep cycle 2, P =.002). During wakefulness, patients showed higher delta/theta activity over the affected regions compared with controls. Conclusions. Patients with focal epilepsy showed a pattern of power increases characterized by a selective slow wave activity enhancement over the epileptic regions during daytime and sleep. This phenomenon was stronger and asymmetric during the first sleep cycles. © EEG and Clinical Neuroscience Society.


Karabanov A.N.,National Institute of Mental Health | Karabanov A.N.,Danish Research Center for Magnetic Resonance | Karabanov A.N.,U.S. National Institutes of Health | Paine R.,U.S. National Institutes of Health | And 6 more authors.
PLoS ONE | Year: 2015

Accumulating evidence suggests that storing speech sounds requires transposing rapidly fluctuating sound waves into more easily encoded oromotor sequences. If so, then the classical speech areas in the caudalmost portion of the temporal gyrus (pSTG) and in the inferior frontal gyrus (IFG) may be critical for performing this acoustic-romotor transposition. We tested this proposal by applying repetitive transcranial magnetic stimulation (rTMS) to each of these left-hemisphere loci, as well as to a nonspeech locus, while participants listened to pseudowords. After 5 minutes these stimuli were re-presented together with new ones in a recognition test. Compared to control-site stimulation, pSTG stimulation produced a highly significant increase in recognition error rate, without affecting reaction time. By contrast, IFG stimulation led only to a weak, non-significant, trend toward recognition memory impairment. Importantly, the impairment after pSTG stimulation was not due to interference with perception, since the same stimulation failed to affect pseudoword discrimination examined with short interstimulus intervals. Our findings suggest that pSTG is essential for transforming speech sounds into stored motor plans for reproducing the sound. Whether or not the IFG also plays a role in speech-sound recognition could not be determined from the present results.


Vilamala A.,Technical University of Denmark | Madsen K.H.,Danish Research Center for Magnetic Resonance | Hansen L.K.,Technical University of Denmark
2017 International Workshop on Pattern Recognition in Neuroimaging, PRNI 2017 | Year: 2017

Functional Magnetic Resonance Imaging (fMRI) relies on multi-step data processing pipelines to accurately determine brain activity; among them, the crucial step of spatial smoothing. These pipelines are commonly suboptimal, given the local optimisation strategy they use, treating each step in isolation. With the advent of new tools for deep learning, recent work has proposed to turn these pipelines into end-to-end learning networks. This change of paradigm offers new avenues to improvement as it allows for a global optimisation. The current work aims at benefitting from this paradigm shift by defining a smoothing step as a layer in these networks able to adaptively modulate the degree of smoothing required by each brain volume to better accomplish a given data analysis task. The viability is evaluated on real fMRI data where subjects did alternate between left and right finger tapping tasks. © 2017 IEEE.


Coulon O.,Aix - Marseille University | Lefevre J.,Aix - Marseille University | Kloppel S.,Albert Ludwigs University of Freiburg | Siebner H.,Danish Research Center for Magnetic Resonance | Mangin J.-F.,CEA Saclay Nuclear Research Center
Proceedings - International Symposium on Biomedical Imaging | Year: 2015

We present in this paper a method to perform a length parameterization of cortical sulcus meshes. Such parameterization allows morphological features to be localized in a normalized way along the length of the sulcus and can be used to perform population studies and group comparisons. Our method uses the second eigenfunction of the Laplace-Beltrami operator, and the resulting parameterization is quasi-isometric. The process is validated on the central sulci of a set of subjects and its efficiency is demonstrated by quantifying morphological differences between left and right-handed subjects. © 2015 IEEE.


PubMed | University of L'Aquila, Biomedical University of Rome, Montreal Neurological Institute and Danish Research Center for Magnetic Resonance
Type: | Journal: Clinical EEG and neuroscience | Year: 2016

Introduction We aimed to test differences between healthy subjects and patients with respect to slow wave activity during wakefulness and sleep. Methods Fifteen patients affected by nonlesional focal epilepsy originating within temporal areas and fourteen matched controls underwent a 24-hour EEG recording. We studied the EEG power spectral density during wakefulness and sleep in delta (1-4 Hz), theta (5-7 Hz), alpha (8-11 Hz), sigma (12-15 Hz), and beta (16-20 Hz) bands. Results During sleep, patients with focal epilepsy showed higher power from delta to beta frequency bands compared with controls. The effect was widespread for alpha band and above, while localized over the affected hemisphere for delta (sleep cycle 1, P = .006; sleep cycle 2, P = .008; sleep cycle 3, P = .017). The analysis of interhemispheric differences showed that the only frequency band stronger over the affected regions was the delta band during the first 2 sleep cycles (sleep cycle 1, P = .014; sleep cycle 2, P = .002). During wakefulness, patients showed higher delta/theta activity over the affected regions compared with controls. Conclusions Patients with focal epilepsy showed a pattern of power increases characterized by a selective slow wave activity enhancement over the epileptic regions during daytime and sleep. This phenomenon was stronger and asymmetric during the first sleep cycles.


Raffin E.,Jean Monnet University | Raffin E.,Danish Research Center for Magnetic Resonance | Giraux P.,Jean Monnet University | Reilly K.T.,French Institute of Health and Medical Research
Movement and Sports Sciences - Science et Motricite | Year: 2013

The phantom limb is a sensory experience that is perceived to originate from the missing part. Amputees report that the phantom limb has certain sensory properties like touch and pain, as well as kinesthetic properties like being able to be moved voluntarily. Phantom limb movements are little-known and from a neuropsychological point of view this form of movements are generally considered to reflect motor imagery rather than motor execution. Here we report findings showing that amputees do distinguish between motor imagery and motor execution with their phantom limb and that this distinction is based both on differences in behavioral performances and in the recruitment of partially distinct brain regions. The study of phantom limb motor perceptions raises important questions about the very nature of the processes underlying the awareness of a movement as being executed or imagined. It also points out some possible mechanisms that support pain relief associated with phantom limb motor training. Interestingly, a good phantom limb motor control is also associated with successful myoelectric prosthesis equipment and a fast relearning of basic movements after hand allografts. © ACAPS, EDP Sciences, 2013.


Chumbley J.R.,University of Zürich | Hulme O.,Danish Research Center for Magnetic Resonance | Kochli H.,University of Zürich | Russell E.,University of Western Ontario | And 3 more authors.
Physiology and Behavior | Year: 2014

Healthy individuals tend to consume available rewards like food and sex. This tendency is attenuated or amplified in most stress-related psychiatric conditions, so we asked if it depends on endogenous levels of the 'canonical stress hormone' cortisol. We unobtrusively quantified how hard healthy heterosexual men would work to consume erotic images of women versus men and also measured their exposure to endogenous cortisol in the prior two months. We used linear models to predict the strength of sexual preference from cortisol level, after accounting for other potential explanations. Heterosexual preference declines with self-reported anhedonia but increases with long term exposure to endogenous cortisol. These results suggest that cortisol may affect reward-related behavior in healthy adults. © 2013.


Roge R.E.,Technical University of Denmark | Madsen K.H.,Danish Research Center for Magnetic Resonance | Schmidt M.N.,Technical University of Denmark | Morup M.,Technical University of Denmark
IEEE International Workshop on Machine Learning for Signal Processing, MLSP | Year: 2015

Functional Magnetic Resonance Imaging has become a central measuring modality to quantify functional activiation of the brain in both task and rest. Most analysis used to quantify functional activation requires supervised approaches as employed in statistical parametric mapping (SPM) to extract maps of task induced functional activations. This requires strong knowledge and assumptions on the BOLD response as a function of activitation while smoothing in general enhances the statistical power but at the cost of spatial resolution. We propose a fully unsupervised approach for the extraction of task activated functional units in multi-subject fMRI data that exploits that regions of task activation are consistent across subjects and can be more reliably inferred than regions that are not activated. We develop a non-parametric Gaussian mixture model that apriori assumes activations are smooth using a Gaussian Process prior while assuming the segmented functional maps are the same across subjects but having individual time-courses and noise variances. To improve inference we propose an enhanced split-merge procedure. We find that our approach well extracts the induced activity of a finger tapping fMRI paradigm with maps that well corresponds to a supervised group SPM analysis. We further find interesting regions that are not activated time locked to the paradigm. Demonstrating that we in a fully unsupervised manner are able to extract the task-induced activations forms a promising framework for the analysis of task fMRI and resting-state data in general where strong knowledge of how the task induces a BOLD response is missing. © 2015 IEEE.

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