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  • 1.
    Björnsdotter, Malin
    et al.
    Department of Physiology, Institute of Neuroscience and Physiology, University of Gothenburg, Sweden.
    Rylander, Karin
    Department of Physiology, Institute of Neuroscience and Physiology, University of Gothenburg, Sweden.
    Wessberg, Johan
    Department of Physiology, Institute of Neuroscience and Physiology, University of Gothenburg, Sweden.
    A Monte Carlo method for locally multivariate brain mapping.2011Ingår i: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 56, nr 2, s. 508-516Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Locally multivariate approaches to functional brain mapping offer a highly appealing complement to conventional statistics, but require restrictive region-of-interest hypotheses, or, in exhaustive search forms (such as the "searchlight" algorithm; Kriegeskorte et al., 2006), are excessively computer intensive. We therefore propose a non-restrictive, comparatively fast yet highly sensitive method based on Monte Carlo approximation principles where locally multivariate maps are computed by averaging across voxelwise condition-discriminative information obtained from repeated stochastic sampling of fixed-size search volumes. On simulated data containing discriminative regions of varying size and contrast-to-noise ratio (CNR), the Monte Carlo method reduced the required computer resources by as much as 75% compared to the searchlight with no reduction in mapping performance. Notably, the Monte Carlo mapping approach not only outperformed the general linear method (GLM), but also produced higher discriminative voxel detection scores than the searchlight irrespective of classifier (linear or nonlinear support vector machine), discriminative region size or CNR. The improved performance was explained by the information-average procedure, and the Monte Carlo approach yielded mapping sensitivities of a few percent lower than an information-average exhaustive search. Finally, we demonstrate the utility of the algorithm on whole-brain, multi-subject functional magnetic resonance imaging (fMRI) data from a tactile study, revealing that the central representation of gentle touch is spatially distributed in somatosensory, insular and visual regions.

  • 2.
    Cardin, Velia
    et al.
    Linköpings universitet, Institutionen för beteendevetenskap och lärande. University College London, Division of Psychology and Language Sciences.
    Smittenaar, Rebecca C.
    University College London, Experimental Psychology.
    Orfanidou, Eleni
    University of Crete, Greece.
    Rönnberg, Jerker
    Linköpings universitet, Institutionen för beteendevetenskap och lärande, Handikappvetenskap. Linköpings universitet, Filosofiska fakulteten.
    Capek, Cheryl M.
    University of Manchester, School of Psychological Sciences.
    Rudner, Mary
    Linköpings universitet, Institutionen för beteendevetenskap och lärande, Handikappvetenskap. Linköpings universitet, Filosofiska fakulteten.
    Woll, Bencie
    University College London, Division of Psychology and Language Sciences.
    Differential activity in Heschl's gyrus between deaf and hearing individuals is due to auditory deprivation rather than language modality2016Ingår i: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 124, s. 96-106Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Sensory cortices undergo crossmodal reorganisation as a consequence of sensory deprivation. Congenital deafness in humans represents a particular case with respect to other types of sensory deprivation, because cortical reorganisation is not only a consequence of auditory deprivation, but also of language-driven mechanisms. Visual crossmodal plasticity has been found in secondary auditory cortices of deaf individuals, but it is still unclear if reorganisation also takes place in primary auditory areas, and how this relates to language modality and auditory deprivation.

    Here, we dissociated the effects of language modality and auditory deprivation on crossmodal plasticity in Heschl's gyrus as a whole, and in cytoarchitectonic region Te1.0 (likely to contain the core auditory cortex). Using fMRI, we measured the BOLD response to viewing sign language in congenitally or early deaf individuals with and without sign language knowledge, and in hearing controls.

    Results show that differences between hearing and deaf individuals are due to a reduction in activation caused by visual stimulation in the hearing group, which is more significant in Te1.0 than in Heschl's gyrus as a whole. Furthermore, differences between deaf and hearing groups are due to auditory deprivation, and there is no evidence that the modality of language used by deaf individuals contributes to crossmodal plasticity in Heschl's gyrus.

  • 3.
    Croy, Ilona
    et al.
    Linköpings universitet, Institutionen för klinisk och experimentell medicin, Avdelningen för neuro- och inflammationsvetenskap. Linköpings universitet, Medicinska fakulteten. University of Gothenburg, Sweden; Technical University of Dresden, Germany.
    Drechsler, Edda
    Technical University of Dresden, Germany.
    Hamilton, Paul
    Linköpings universitet, Institutionen för klinisk och experimentell medicin, Avdelningen för neuro- och inflammationsvetenskap. Linköpings universitet, Medicinska fakulteten. Linköpings universitet, Centrum för social och affektiv neurovetenskap (CSAN).
    Hummel, Thomas
    Technical University of Dresden, Germany.
    Olausson, Håkan
    Linköpings universitet, Institutionen för klinisk och experimentell medicin, Avdelningen för neuro- och inflammationsvetenskap. Linköpings universitet, Medicinska fakulteten. University of Gothenburg, Sweden.
    Olfactory modulation of affective touch processing - A neurophysiological investigation2016Ingår i: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 135, s. 135-141Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Touch can be highly emotional, and depending on the environment, it can be perceived as pleasant and comforting or disgusting and dangerous. Here, we studied the impact of context on the processing of tactile stimuli using a functional magnetic resonance imaging (fMRI) paradigm. This was achieved by embedding tactile stimulation in a variable olfactory environment. Twenty people were scanned with BOLD fMRI while receiving the following stimulus blocks: Slow stroking Touch, Civette odor (feces like), Rose odor, Touch + Civette, and Touch + Rose. Ratings of pleasantness and intensity of tactile stimuli and ratings of disgust and intensity of olfactory stimuli were collected. The impact of the olfactory context on the processing of touch was studied using covariance analyses. Coupling between olfactory processing and somatosensory processing areas was assessed with psychophysiological interaction analysis (PPI). A subjectively disgusting olfactory environment significantly reduced the perceived pleasantness of touch. The touch fMRI activation in the secondary somatosensory cortex, operculum 1 (OP1), was positively correlated with the disgust towards the odors. Decreased pleasantness of touch was related to decreased posterior insula activity. PPI analysis revealed a significant interaction between the OP1, posterior insula, and regions processing the disgust of odors (orbitofrontal cortex and amygdala). We conclude that the disgust evaluation of the olfactory environment moderates neural reactivity in somatosensory regions by upregulation of the OP1 and downregulation of the posterior insula. This adaptive regulation of affective touch processing may facilitate adaptive reaction to a potentially harmful stimulus. (C) 2016 Elsevier Inc. All rights reserved.

  • 4.
    Dela Haije, Tom
    et al.
    Univ Copenhagen, Denmark.
    Özarslan, Evren
    Linköpings universitet, Institutionen för medicinsk teknik, Avdelningen för medicinsk teknik. Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Feragen, Aasa
    Tech Univ Denmark, Denmark.
    Enforcing necessary non-negativity constraints for common diffusion MRI models using sum of squares programming2020Ingår i: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 209, artikel-id 116405Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In this work we investigate the use of sum of squares constraints for various diffusion-weighted MRI models, with a goal of enforcing strict, global non-negativity of the diffusion propagator. We formulate such constraints for the mean apparent propagator model and for spherical deconvolution, guaranteeing strict non-negativity of the corresponding diffusion propagators. For the cumulant expansion similar constraints cannot exist, and we instead derive a set of auxiliary constraints that are necessary but not sufficient to guarantee non-negativity. These constraints can all be verified and enforced at reasonable computational costs using semidefinite programming. By verifying our constraints on standard reconstructions of the different models, we show that currently used weak constraints are largely ineffective at ensuring non-negativity. We further show that if strict non-negativity is not enforced then estimated model parameters may suffer from significant errors, leading to serious inaccuracies in important derived quantities such as the main fiber orientations, mean kurtosis, etc. Finally, our experiments confirm that the observed constraint violations are mostly due to measurement noise, which is difficult to mitigate and suggests that properly constrained optimization should currently be considered the norm in many cases.

  • 5.
    Eklund, Anders
    et al.
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Andersson, Mats
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Josephson, Camilla
    Linköpings universitet, Institutionen för ekonomisk och industriell utveckling, Nationalekonomi. Linköpings universitet, Filosofiska fakulteten.
    Johannesson, Magnus
    Stockholm School of Economics.
    Knutsson, Hans
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Does Parametric fMRI Analysis with SPM Yield Valid Results? - An Empirical Study of 1484 Rest Datasets2012Ingår i: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 61, nr 3, s. 565-578Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The validity of parametric functional magnetic resonance imaging (fMRI) analysis has only been reported for simulated data.Recent advances in computer science and data sharing make it possible to analyze large amounts of real fMRI data. In this study,1484 rest datasets have been analyzed in SPM8, to estimate true familywise error rates. For a familywise significance threshold of5%, significant activity was found in 1% - 70% of the 1484 rest datasets, depending on repetition time, paradigm and parametersettings. This means that parametric significance thresholds in SPM both can be conservative or very liberal. The main reason forthe high familywise error rates seems to be that the global AR(1) auto correlation correction in SPM fails to model the spectra ofthe residuals, especially for short repetition times. The findings that are reported in this study cannot be generalized to parametricfMRI analysis in general, other software packages may give different results. By using the computational power of the graphicsprocessing unit (GPU), the 1484 rest datasets were also analyzed with a random permutation test. Significant activity was thenfound in 1% - 19% of the datasets. These findings speak to the need for a better model of temporal correlations in fMRI timeseries.

  • 6.
    Eklund, Anders
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Statistik. Linköpings universitet, Institutionen för medicinsk teknik, Avdelningen för medicinsk teknik. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Filosofiska fakulteten.
    Lindqvist, Martin A
    Department of Biostatistics, Johns Hopkins University, Baltimore, USA.
    Villani, Mattias
    Linköpings universitet, Institutionen för datavetenskap, Statistik. Linköpings universitet, Filosofiska fakulteten.
    A Bayesian Heteroscedastic GLM with Application to fMRI Data with Motion Spikes2017Ingår i: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 155, s. 354-369Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    We propose a voxel-wise general linear model with autoregressive noise and heteroscedastic noise innovations (GLMH) for analyzing functional magnetic resonance imaging (fMRI) data. The model is analyzed from a Bayesian perspective and has the benefit of automatically down-weighting time points close to motion spikes in a data-driven manner. We develop a highly efficient Markov Chain Monte Carlo (MCMC) algorithm that allows for Bayesian variable selection among the regressors to model both the mean (i.e., the design matrix) and variance. This makes it possible to include a broad range of explanatory variables in both the mean and variance (e.g., time trends, activation stimuli, head motion parameters and their temporal derivatives), and to compute the posterior probability of inclusion from the MCMC output. Variable selection is also applied to the lags in the autoregressive noise process, making it possible to infer the lag order from the data simultaneously with all other model parameters. We use both simulated data and real fMRI data from OpenfMRI to illustrate the importance of proper modeling of heteroscedasticity in fMRI data analysis. Our results show that the GLMH tends to detect more brain activity, compared to its homoscedastic counterpart, by allowing the variance to change over time depending on the degree of head motion.

  • 7.
    Esteban-Cornejo, Irene
    et al.
    Northeastern Univ, MA 02115 USA; Univ Granada, Spain.
    Mora-Gonzalez, Jose
    Univ Granada, Spain.
    Cadenas-Sanchez, Cristina
    Univ Granada, Spain.
    Contreras-Rodriguez, Oren
    Bellvitge Biomed Res Inst IDIBELL, Spain; Ctr Invest Biomed Red Salud Mental CIBERSAM, Spain.
    Verdejo-Roman, Juan
    Univ Granada, Spain.
    Henriksson, Pontus
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för samhällsmedicin. Linköpings universitet, Medicinska fakulteten. Univ Granada, Spain; Karolinska Inst, Sweden.
    Migueles, Jairo H.
    Univ Granada, Spain.
    Rodriguez-Ayllon, Maria
    Univ Granada, Spain.
    Molina-Garcia, Pablo
    Univ Granada, Spain.
    Suo, Chao
    Monash Univ, Australia.
    Hillman, Charles H.
    Northeastern Univ, MA 02115 USA.
    Kramer, Arthur F.
    Northeastern Univ, MA 02115 USA; Univ Illinois, IL USA.
    Erickson, Kirk I
    Univ Pittsburgh, PA 15260 USA.
    Catena, Andres
    Univ Granada, Spain.
    Verdejo-Garcia, Antonio
    Monash Univ, Australia.
    Ortega, Francisco B.
    Univ Granada, Spain; Karolinska Inst, Sweden.
    Fitness, cortical thickness and surface area in overweight/obese children: The mediating role of body composition and relationship with intelligence2019Ingår i: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 186, s. 771-781Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Cortical thickness and surface area are thought to be genetically unrelated and shaped by independent neurobiological events suggesting that they should be considered separately in morphometric analyses. Although the developmental trajectories of cortical thickness and surface area may differ across brain regions and ages, there is no consensus regarding the relationships of physical fitness with cortical thickness and surface area as well as for its subsequent influence on intelligence. Thus, this study examines: (i) the associations of physical fitness components (i.e., cardiorespiratory fitness, speed-agility and muscular fitness) with overall and regional cortical thickness and surface area; (ii) whether body composition indicators (i.e., body mass index, fat-free mass index and fat mass index) mediate these associations; and (iii) the association of physical fitness and cortical thickness with intelligence in overweight/obese children. A total of 101 overweight/obese children aged 8-11 years were recruited in Granada, Spain. The physical fitness components were assessed following the ALPHA health-related fitness test battery. T1-weighted images were acquired with a 3.0 Tesla Siemens Magnetom Tim Trio system. We used FreeSurfer software version 5.3.0 to assess cortical thickness (mm) and surface area (mm(2)). The main results showed that cardiorespiratory fitness and speed-agility were related to overall cortical thickness (beta = 0.321 and beta = 0.302, respectively; both P amp;lt; 0.05), and in turn, cortical thickness was associated with higher intelligence (beta = 0.198, P amp;lt; 0.05). Muscular fitness was not related to overall cortical thickness. None of the three physical fitness components were related to surface area (p amp;gt; 0.05). The associations of cardiorespiratory fitness and speed-agility with overall cortical thickness were mediated by fat mass index (56.86% amp; 62.28%, respectively). In conclusion, cardiorespiratory fitness and speed-agility, but not muscular fitness, are associated with overall cortical thickness, and in turn, thicker brain cortex is associated with higher intelligence in overweight/obese children. Yet, none of the three physical fitness components were related to surface area. Importantly, adiposity may hinder the benefits of cardiorespiratory fitness and speed-agility on cortical thickness. Understanding individual differences in brain morphology may have important implications for educators and policy makers who aim to determine policies and interventions to maximize academic learning and occupational success later in life.

  • 8.
    Friman, Ola
    et al.
    Linköpings universitet, Institutionen för medicinsk teknik. Linköpings universitet, Tekniska högskolan.
    Borga, Magnus
    Linköpings universitet, Institutionen för medicinsk teknik. Linköpings universitet, Tekniska högskolan.
    Lundberg, Peter
    Östergötlands Läns Landsting, Kirurgi- och onkologicentrum, Radiofysikavdelningen. Linköpings universitet, Hälsouniversitetet.
    Knutsson, Hans
    Linköpings universitet, Institutionen för medicinsk teknik. Linköpings universitet, Tekniska högskolan.
    Adaptive analysis of fMRI data2003Ingår i: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 19, nr 3, s. 837-845Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This article introduces novel and fundamental improvements of fMRI data analysis. Central is a technique termed constrained canonical correlation analysis, which can be viewed as a natural extension and generalization of the popular general linear model method. The concept of spatial basis filters is presented and shown to be a very successful way of adaptively filtering the fMRI data. A general method for designing suitable hemodynamic response models is also proposed and incorporated into the constrained canonical correlation approach. Results that demonstrate how each of these parts significantly improves the detection of brain activity, with a computation time well within limits for practical use, are provided.

  • 9.
    Friman, Ola
    et al.
    Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
    Borga, Magnus
    Linköpings universitet, Institutionen för medicinsk teknik. Linköpings universitet, Tekniska högskolan.
    Lundberg, Peter
    Linköpings universitet, Institutionen för medicin och hälsa, Medicinsk radiofysik. Linköpings universitet, Hälsouniversitetet.
    Knutsson, Hans
    Linköpings universitet, Institutionen för medicinsk teknik. Linköpings universitet, Tekniska högskolan.
    Detection and detrending in fMRI data analysis2004Ingår i: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 22, nr 2, s. 645-655Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This article addresses the impact that colored noise, temporal filtering, and temporal detrending have on the fMRI analysis situation. Specifically, it is shown why the detection of event-related designs benefit more from pre-whitening than blocked designs in a colored noise structure. Both theoretical and empirical results are provided. Furthermore, a novel exploratory method for producing drift models that efficiently capture trends and drifts in the fMRI data is introduced. A comparison to currently employed detrending approaches is presented. It is shown that the novel exploratory model is able to remove a major part of the slowly varying drifts that are abundant in fMRI data. The value of such a model lies in its ability to remove drift components that otherwise would have contributed to a colored noise structure in the voxel time series.

  • 10.
    Friman, Ola
    et al.
    Linköpings universitet, Institutionen för medicinsk teknik. Linköpings universitet, Tekniska högskolan.
    Borga, Magnus
    Linköpings universitet, Institutionen för medicinsk teknik. Linköpings universitet, Tekniska högskolan.
    Lundberg, Peter
    Östergötlands Läns Landsting, Kirurgi- och onkologicentrum, Radiofysikavdelningen. Linköpings universitet, Tekniska högskolan.
    Knutsson, Hans
    Linköpings universitet, Institutionen för medicinsk teknik. Linköpings universitet, Tekniska högskolan.
    Detection of neural activity in fMRI using maximum correlation modeling2002Ingår i: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 15, nr 2, s. 386-395Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    A technique for detecting neural activity in functional MRI data is introduced. It is based on a novel framework termed maximum correlation modeling. The method employs a spatial filtering approach that adapts to the local activity patterns, which results in an improved detection sensitivity combined with good specificity. A spatially varying hemodynamic response is simultaneously modelled by a sum of two gamma functions. Comparisons to traditional analysis methods are made using both synthetic and real data. The results indicate that the maximum correlation modeling approach is a strong alternative for analyzing fMRI data.

  • 11.
    Friman, Ola
    et al.
    Linköpings universitet, Institutionen för medicinsk teknik. Linköpings universitet, Tekniska högskolan.
    Borga, Magnus
    Linköpings universitet, Institutionen för medicinsk teknik. Linköpings universitet, Tekniska högskolan.
    Lundberg, Peter
    Östergötlands Läns Landsting, Kirurgi- och onkologicentrum, Radiofysikavdelningen. Linköpings universitet, Hälsouniversitetet.
    Knutsson, Hans
    Linköpings universitet, Institutionen för medicinsk teknik. Linköpings universitet, Tekniska högskolan.
    Exploratory fMRI analysis by autocorrelation maximization2002Ingår i: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 16, nr 2, s. 454-464Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    A novel and computationally efficient method for exploratory analysis of functional MRI data is presented. The basic idea is to reveal underlying components in the fMRI data that have maximum autocorrelation. The tool for accomplishing this task is Canonical Correlation Analysis. The relation to Principal Component Analysis and Independent Component Analysis is discussed and the performance of the methods is compared using both simulated and real data.

  • 12.
    Gentile, Giovanni
    et al.
    Karolinska Institute, Sweden.
    Åberg, Malin
    Linköpings universitet, Institutionen för klinisk och experimentell medicin, Avdelningen för neuro- och inflammationsvetenskap. Linköpings universitet, Medicinska fakulteten. Karolinska Institute, Sweden.
    Petkova, Valeria I.
    Karolinska Institute, Sweden.
    Abdulkarim, Zakaryah
    Karolinska Institute, Sweden.
    Henrik Ehrsson, H.
    Karolinska Institute, Sweden.
    Patterns of neural activity in the human ventral premotor cortex reflect a whole-body multisensory percept2015Ingår i: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 109, s. 328-340Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Previous research has shown that the integration of multisensory signals from the body in fronto-parietal association areas underlies the perception of a body part as belonging to ones physical self. What are the neural mechanisms that enable the perception of ones entire body as a unified entity? In one behavioral and one fMRI multivoxel pattern analysis experiment, we used a full-body illusion to investigate how congruent visuo-tactile signals from a single body part facilitate the emergence of the sense of ownership of the entire body. To elicit this illusion, participants viewed the body of a mannequin from the first-person perspective via head-mounted displays while synchronous touches were applied to the hand, abdomen, or leg of the bodies of the participant and the mannequin; asynchronous visuo-tactile stimuli served as controls. The psychometric data indicated that the participants perceived ownership of the entire artificial body regardless of the body segment that received the synchronous visuo-tactile stimuli. Based on multivoxel pattern analysis, we found that the neural responses in the left ventral premotor cortex displayed illusion-specific activity patterns that generalized across all tested pairs of body parts. Crucially, a tripartite generalization analysis revealed the whole-body specificity of these premotor activity patterns. Finally, we also identified multivoxel patterns in the premotor, intraparietal, and lateral occipital cortices and in the putamen that reflected multisensory responses specific to individual body parts. Based on these results, we propose that the dynamic formation of a whole-body percept may be mediated by neuronal populations in the ventral premotor cortex that contain visuo-tactile receptive fields encompassing multiple body segments.

  • 13.
    Jonsson, Emma H.
    et al.
    Univ Gothenburg, Sweden.
    Kotilahti, Kalle
    Aalto Univ, Finland.
    Heiskala, Juha
    Univ Helsinki, Finland.
    Wasling, Helena Backlund
    Univ Gothenburg, Sweden.
    Olausson, Håkan
    Linköpings universitet, Institutionen för klinisk och experimentell medicin, Centrum för social och affektiv neurovetenskap. Linköpings universitet, Medicinska fakulteten. Region Östergötland, Sinnescentrum, Neurofysiologiska kliniken US. Univ Gothenburg, Sweden.
    Croy, Ilona
    Tech Univ Dresden, Germany.
    Mustaniemi, Hanna
    Aalto Univ, Finland.
    Hiltunen, Petri
    Aalto Univ, Finland.
    Tuulari, Jetro J.
    Univ Turku, Finland.
    Scheinin, Noora M.
    Univ Turku, Finland; Turku Univ Hosp, Finland.
    Karlsson, Linnea
    Univ Turku, Finland; Turku Univ Hosp, Finland.
    Karlsson, Hasse
    Univ Turku, Finland; Turku Univ Hosp, Finland.
    Nissila, Ilkka
    Aalto Univ, Finland.
    Affective and non-affective touch evoke differential brain responses in 2-month-old infants2018Ingår i: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 169, s. 162-171Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Caressing touch is an effective way to communicate emotions and to create social bonds. It is also one of the key mediators of early parental bonding. The caresses are generally thought to represent a social form of touching and indeed, slow, gentle brushing is encoded in specialized peripheral nerve fibers, the C-tactile (CT) afferents. In adults, areas such as the posterior insula and superior temporal sulcus are activated by affective, slow stroking touch but not by fast stroking stimulation. However, whether these areas are activated in infants, after social tactile stimulation, is unknown. In this study, we compared the total hemoglobin responses measured with diffuse optical tomography (DOT) in the left hemisphere following slow and fast stroking touch stimulation in 16 2-month-old infants. We compared slow stroking (optimal CT afferent stimulation) to fast stroking (non-optimal CT stimulation). Activated regions were delineated using two methods: one based on contrast between the two conditions, and the other based on voxel-based statistical significance of the difference between the two conditions. The first method showed a single activation cluster in the temporal cortex with center of gravity in the middle temporal gyrus where the total hemoglobin increased after the slow stroking relative to the fast stroking (p = 0.04 uncorrected). The second method revealed a cluster in the insula with an increase in total hemoglobin in the insular cortex in response to slow stroking relative to fast stroking (p = 0.0005 uncorrected; p = 0.04 corrected for multiple comparisons). These activation clusters encompass areas that are involved in processing of affective, slow stroking touch in the adult brain. We conclude that the infant brain shows a pronounced and adult-like response to slow stroking touch compared to fast stroking touch in the insular cortex but the expected response in the primary somatosensory cortex was not found at this age. The results imply that emotionally valent touch is encoded in the brain in adult-like manner already soon after birth and this suggests a potential for involvement of touch in bonding with the caretaker.

  • 14.
    Kitada, Ryo
    et al.
    National Institute for Physiological Sciences, Okazaki, Japan.
    Johnsrude, Ingrid
    Queen's University, Kingston, Canada.
    Kochiyama, Takanori
    ATR Brain Activity Imaging Center, Seika-cho, Japan.
    Lederman, Susan J.
    Queen's University, Kingston, Canada.
    Brain networks involved in haptic and visual identification of facial expressions of emotion: An fMRI study2010Ingår i: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 49, nr 2, s. 1677-1689Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Previous neurophysiological and neuroimaging studies have shown that a cortical network involving the inferior frontal gyrus (IFG), inferior parietal lobe (IPL) and cortical areas in and around the posterior superior temporal sulcus (pSTS) region is employed in action understanding by vision and audition. However, the brain regions that are involved in action understanding by touch are unknown. Lederman et al. (2007) recently demonstrated that humans can haptically recognize facial expressions of emotion (FEE) surprisingly well. Here, we report a functional magnetic resonance imaging (fMRI) study in which we test the hypothesis that the IFG, IPL and pSTS regions are involved in haptic, as well as visual, FEE identification. Twenty subjects haptically or visually identified facemasks with three different FEEs (disgust, neutral and happiness) and casts of shoes (shoes) of three different types. The left posterior middle temporal gyrus, IPL, IFG and bilateral precentral gyrus were activated by FEE identification relative to that of shoes, regardless of sensory modality. By contrast, an inferomedial part of the left superior parietal lobule was activated by haptic, but not visual, FEE identification. Other brain regions, including the lingual gyrus and superior frontal gyrus, were activated by visual identification of FEEs, relative to haptic identification of FEEs. These results suggest that haptic and visual FEE identification rely on distinct but overlapping neural substrates including the IFG, IPL and pSTS region.

  • 15.
    Ning, Lipeng
    et al.
    Harvard Medical Sch, MA 02115 USA.
    Özarslan, Evren
    Linköpings universitet, Institutionen för medicinsk teknik, Avdelningen för medicinsk teknik. Linköpings universitet, Tekniska fakulteten.
    Westin, Carl-Fredrik
    Harvard Medical Sch, MA 02115 USA.
    Rathi, Yogesh
    Harvard Medical Sch, MA 02115 USA.
    Precise Inference and Characterization of Structural Organization (PICASO) of tissue from molecular diffusion2017Ingår i: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 146, s. 452-473Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Inferring the microstructure of complex media from the diffusive motion of molecules is a challenging problem in diffusion physics. In this paper, we introduce a novel representation of diffusion MRI (dMRI) signal from tissue with spatially-varying diffusivity using a diffusion disturbance function. This disturbance function contains information about the (intra-voxel) spatial fluctuations in diffusivity due to restrictions, hindrances and tissue heterogeneity of the underlying tissue substrate. We derive the short- and long-range disturbance coefficients from this disturbance function to characterize the tissue structure and organization. Moreover, we provide an exact relation between the disturbance coefficients and the time-varying moments of the diffusion propagator, as well as their relation to specific tissue microstructural information such as the intra-axonal volume fraction and the apparent axon radius. The proposed approach is quite general and can model dMRI signal for any type of gradient sequence (rectangular, oscillating, etc.) without using the Gaussian phase approximation. The relevance of the proposed PICASO model is explored using Monte-Carlo simulations and in-vivo dMRI data. The results show that the estimated disturbance coefficients can distinguish different types of microstructural organization of axons.

  • 16.
    Rudner, Mary
    et al.
    Linköpings universitet, Institutionen för nervsystem och rörelseorgan. Linköpings universitet, Hälsouniversitetet.
    Cedefamn, Jonny
    Friman, Ola
    Linköpings universitet, Institutionen för medicinsk teknik, Fysiologisk mätteknik. Linköpings universitet, Tekniska högskolan.
    Knutsson, Hans
    Linköpings universitet, Institutionen för medicinsk teknik, Fysiologisk mätteknik. Linköpings universitet, Tekniska högskolan.
    Lundberg, Peter
    Linköpings universitet, Hälsouniversitetet. Linköpings universitet, Institutionen för medicin och vård, Radiofysik. Östergötlands Läns Landsting, Kirurgi- och onkologicentrum, Radiofysikavdelningen.
    Söderfeldt, Birgitta
    Linköpings universitet, Hälsouniversitetet. Linköpings universitet, Institutionen för nervsystem och rörelseorgan. Östergötlands Läns Landsting, Närsjukvården i centrala Östergötland, Neurologiska kliniken.
    Are levels of language processing reflected in neural activation? - An fMRI study.2001Ingår i: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 13, nr 6Artikel i tidskrift (Refereegranskat)
  • 17.
    Saager, Rolf B.
    et al.
    The Institute of Optics, University of Rochester, Rochester, NY 14627, USA.
    Telleri, Nicole L.
    Department of Biomedical Engineering, University of Rochester, Rochester, NY 14627, USA.
    Berger, Andrew J.
    The Institute of Optics, University of Rochester, Rochester, NY 14627, USA.
    Two-detector Corrected Near Infrared Spectroscopy (C-NIRS) detects hemodynamic activation responses more robustly than single-detector NIRS2011Ingår i: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 55, nr 4, s. 1679-1685Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In near-infrared spectroscopy (NIRS) of human cerebral hemodynamics, detection of stimulus-related responses is confounded by the presence of unrelated trends in both the brain and the overlying scalp. A proposed strategy for reducing hemodynamic noise has been to record “scalp only” trends simultaneously via a second shorter-separation detector (~5 mm rather than ~30 mm) and perform a subtraction (C-NIRS, for “corrected near-infrared spectroscopy”). To compare the single- and dual-detector strategies, a 21-volunteer study of visual stimulation responses (6 stimulation blocks and 8 recording channels per measurement run) has been conducted. Activation-flagged channels were defined based upon (a) the significance (p-value) of the average rise in oxyhemoglobin concentration and (b) the average signal-to-noise over 6 stimulation epochs. At reasonable thresholds (p < 0.025, SNR> 1), the C-NIRS method increased the number of activation-flagged channels from 47 to 66, an increase of 40%, adding 24 channels and eliminating only 5. Of the 71 channels that were activation-flagged by at least one modality, the C-NIRS time series exhibited more significant oxyhemoglobin rise in 80% of such channels, and better signal-to-noise in 73%. In addition, single-subject C-NIRS stimulus responses were more consistent than NIRS over the six stimulation epochs, with significantly lower coefficients of variation in both amplitude and latency (i.e.  time between stimulus onset and maximum hemoglobin rise). These results demonstrate that two-detector C-NIRS provides a straightforward way of (a) removing hemodynamic interference from NIRS data, (b) increasing the detection rate of cerebrally-unique responses, and (c) improving the quality of those recorded responses. Parallel insights regarding deoxyhemoglobin trends could not be drawn from this data set but should be attainable in future studies with higher signal to noise ratios.

  • 18.
    Sailer, Uta
    et al.
    University of Gothenburg, Sweden; University of Oslo, Norway.
    Triscoli, Chantal
    University of Gothenburg, Sweden; Sahlgrens University Hospital, Sweden.
    Haggblad, Gisela
    Gothenburg University, Sweden.
    Hamilton, Paul
    Linköpings universitet, Institutionen för klinisk och experimentell medicin, Avdelningen för neuro- och inflammationsvetenskap. Linköpings universitet, Medicinska fakulteten. Linköpings universitet, Centrum för social och affektiv neurovetenskap (CSAN).
    Olausson, Håkan
    Linköpings universitet, Institutionen för klinisk och experimentell medicin, Avdelningen för neuro- och inflammationsvetenskap. Linköpings universitet, Medicinska fakulteten. Sahlgrens University Hospital, Sweden.
    Croy, Ilona
    Linköpings universitet, Institutionen för klinisk och experimentell medicin, Avdelningen för neuro- och inflammationsvetenskap. Linköpings universitet, Medicinska fakulteten. Technical University of Dresden, Germany.
    Temporal dynamics of brain activation during 40 minutes of pleasant touch2016Ingår i: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 139, s. 360-367Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Introduction: Touch is important for individuals subjective well-being, is typically rewarding, and is one of few sensory stimuli which are experienced as pleasant for a rather long time. This study tracked brain activation during slow stroking stimulation of the arm that was applied continuously for 40 min - a much longer time than what previous studies have investigated. Methods: 25 subjects were stroked for 40 min with a soft brush while they were scanned with functional Magnetic Resonance Imaging, and rated the perceived pleasantness of the brush stroking. Two resting baselines were included. Whole brain-based analyses investigated the neural response to long-lasting stroking. Results: Stroking was perceived as pleasant throughout scanning and activated areas that were previously found to be involved in the processing of pleasant touch. Activation in primary somatosensory cortex (S1) and S2, subdivision OP1, decreased over time, whereas activation in orbito-frontal gyrus (OFC) and putamen strongly increased until reaching a plateau after approximately 20 min. Similarly, functional connectivity of posterior insula with middle cingulate and striatal regions increased over time. Discussion: Long-lasting stroking was processed in similar areas as shorter-lasting stroking. The decreased activation in somatosensory cortices over time may represent stimulus habituation, whereas increased activation in OFC and putamen may relate to the stimulations subjective reward value. This involvement of reward-related brain circuits can facilitate maintenance of long-lasting social touch interactions. (C) 2016 The Authors. Published by Elsevier Inc.

  • 19.
    Sidén, Per
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Statistik. Linköpings universitet, Filosofiska fakulteten.
    Eklund, Anders
    Linköpings universitet, Institutionen för datavetenskap, Statistik. Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Filosofiska fakulteten.
    Bolin, David
    Division of Mathematical Statistics, Department of Mathematical Sciences, Chalmers and University of Gothenburg, Göteborg, Sweden.
    Villani, Mattias
    Linköpings universitet, Institutionen för datavetenskap, Statistik. Linköpings universitet, Filosofiska fakulteten.
    Fast Bayesian whole-brain fMRI analysis with spatial 3D priors2017Ingår i: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 146, s. 211-225Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Spatial whole-brain Bayesian modeling of task-related functional magnetic resonance imaging (fMRI) is a great computational challenge. Most of the currently proposed methods therefore do inference in subregions of the brain separately or do approximate inference without comparison to the true posterior distribution. A popular such method, which is now the standard method for Bayesian single subject analysis in the SPM software, is introduced in Penny et al. (2005b). The method processes the data slice-by-slice and uses an approximate variational Bayes (VB) estimation algorithm that enforces posterior independence between activity coefficients in different voxels. We introduce a fast and practical Markov chain Monte Carlo (MCMC) scheme for exact inference in the same model, both slice-wise and for the whole brain using a 3D prior on activity coefficients. The algorithm exploits sparsity and uses modern techniques for efficient sampling from high-dimensional Gaussian distributions, leading to speed-ups without which MCMC would not be a practical option. Using MCMC, we are for the first time able to evaluate the approximate VB posterior against the exact MCMC posterior, and show that VB can lead to spurious activation. In addition, we develop an improved VB method that drops the assumption of independent voxels a posteriori. This algorithm is shown to be much faster than both MCMC and the original VB for large datasets, with negligible error compared to the MCMC posterior.

  • 20.
    Sjölund, Jens
    et al.
    Linköpings universitet, Institutionen för medicinsk teknik, Avdelningen för medicinsk teknik. Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Elekta Instrument, Stockholm, Sweden.
    Eklund, Anders
    Linköpings universitet, Institutionen för medicinsk teknik, Avdelningen för medicinsk teknik. Linköpings universitet, Institutionen för datavetenskap, Statistik och maskininlärning. Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Özarslan, Evren
    Linköpings universitet, Institutionen för medicinsk teknik, Avdelningen för medicinsk teknik. Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Herberthson, Magnus
    Linköpings universitet, Matematiska institutionen, Matematik och tillämpad matematik. Linköpings universitet, Tekniska fakulteten.
    Bånkestad, Maria
    RISE SICS, Kista, Sweden.
    Knutsson, Hans
    Linköpings universitet, Institutionen för medicinsk teknik, Avdelningen för medicinsk teknik. Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Bayesian uncertainty quantification in linear models for diffusion MRI2018Ingår i: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 175, s. 272-285Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Diffusion MRI (dMRI) is a valuable tool in the assessment of tissue microstructure. By fitting a model to the dMRI signal it is possible to derive various quantitative features. Several of the most popular dMRI signal models are expansions in an appropriately chosen basis, where the coefficients are determined using some variation of least-squares. However, such approaches lack any notion of uncertainty, which could be valuable in e.g. group analyses. In this work, we use a probabilistic interpretation of linear least-squares methods to recast popular dMRI models as Bayesian ones. This makes it possible to quantify the uncertainty of any derived quantity. In particular, for quantities that are affine functions of the coefficients, the posterior distribution can be expressed in closed-form. We simulated measurements from single- and double-tensor models where the correct values of several quantities are known, to validate that the theoretically derived quantiles agree with those observed empirically. We included results from residual bootstrap for comparison and found good agreement. The validation employed several different models: Diffusion Tensor Imaging (DTI), Mean Apparent Propagator MRI (MAP-MRI) and Constrained Spherical Deconvolution (CSD). We also used in vivo data to visualize maps of quantitative features and corresponding uncertainties, and to show how our approach can be used in a group analysis to downweight subjects with high uncertainty. In summary, we convert successful linear models for dMRI signal estimation to probabilistic models, capable of accurate uncertainty quantification.

  • 21.
    Skinbjerg, Mette
    et al.
    National Institute of Mental Health, Bethesda, MD, USA.
    Liow, Jeih-San
    National Institute of Mental Health, Bethesda, MD, USA.
    Seneca, Nicholas
    National Institute of Mental Health, Bethesda, MD, USA.
    Hong, Jinsoo
    National Institute of Mental Health, Bethesda, MD, USA.
    Lu, Shuiyu
    National Institute of Mental Health, Bethesda, MD, USA.
    Thorsell, Annika
    National Institute on Alcohol Abuse and Alcoholism, NIH; Bethesda, MD, USA.
    Heilig, Markus
    National Institute on Alcohol Abuse and Alcoholism, NIH; Bethesda, MD, USA.
    Pike, Victor W.
    National Institute of Mental Health, Bethesda, MD, USA.
    Halldin, Christer
    Karolinska Institutet, Stockholm, Sweden.
    Sibley, David R.
    National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA.
    Innis, Robert B.
    National Institute of Mental Health, Bethesda, MD, USA.
    D2 dopamine receptor internalization prolongs the decrease of radioligand binding after amphetamine: a PET study in a receptor internalization-deficient mouse model2010Ingår i: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 50, nr 4, s. 1402-1407Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Dopamine released by amphetamine decreases the in vivo binding of PET radioligands to the dopamine D(2) receptor. Although concentrations of extracellular dopamine largely return to baseline within 1 to 2 h after amphetamine treatment, radioligand binding remains decreased for several hours. The purpose of this study was to determine whether the prolonged decrease of radioligand binding after amphetamine administration is caused by receptor internalization. To distinguish dopamine displacement from receptor internalization, we used wild-type and arrestin3 (arr3) knockout mice, which are incapable of internalizing D(2) receptors. In addition, we used both the D(2) selective agonist [(11)C]MNPA (which is thought to bind to the high affinity state of the receptor) and the D(2) selective antagonist [(18)F]fallypride (which does not differentiate between high and low affinity state). After an initial baseline scan, animals were divided in three groups for a second scan: either 30 min or 4 h after amphetamine administration (3 mg/kg, i.p.) or as retest. At 30 min, [(11)C]MNPA showed greater displacement than [(18)F]fallypride, but each radioligand gave similar displacement in knockout and wild-type mice. At 4 h, the binding of both radioligands returned to baseline in arr3 knockout mice, but remained decreased in wild-type mice. Radioligand binding was unaltered on retest scanning. Our results suggest that the prolonged decrease of radioligand binding after amphetamine is mainly due to internalization of the D(2) receptor rather than dopamine displacement. In addition, this study demonstrates the utility of small animal PET to study receptor trafficking in vivo in genetically modified mice.

  • 22.
    Sten, Sebastian
    et al.
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Medicinska fakulteten. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Lundengård, Karin
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Medicinska fakulteten. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Witt, Suzanne Tyson
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Medicinska fakulteten.
    Cedersund, Gunnar
    Linköpings universitet, Institutionen för medicinsk teknik, Avdelningen för medicinsk teknik. Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Institutionen för klinisk och experimentell medicin. Linköpings universitet, Medicinska fakulteten.
    Elinder, Fredrik
    Linköpings universitet, Institutionen för klinisk och experimentell medicin, Avdelning för neurobiologi. Linköpings universitet, Medicinska fakulteten.
    Engström, Maria
    Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Medicinska fakulteten. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Neural inhibition can explain negative BOLD responses: A mechanistic modelling and fMRI study2017Ingår i: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 158, s. 219-231Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Functional magnetic resonance imaging (fMRI) of hemodynamic changes captured in the blood oxygen level-dependent (BOLD) response contains information of brain activity. The BOLD response is the result of a complex neurovascular coupling and comes in at least two fundamentally different forms: a positive and a negative deflection. Because of the complexity of the signaling, mathematical modelling can provide vital help in the data analysis. For the positive BOLD response, there are plenty of mathematical models, both physiological and phenomenological. However, for the negative BOLD response, no physiologically based model exists. Here, we expand our previously developed physiological model with the most prominent mechanistic hypothesis for the negative BOLD response: the neural inhibition hypothesis. The model was trained and tested on experimental data containing both negative and positive BOLD responses from two studies: 1) a visual-motor task and 2) a workin-gmemory task in conjunction with administration of the tranquilizer diazepam. Our model was able to predict independent validation data not used for training and provides a mechanistic underpinning for previously observed effects of diazepam. The new model moves our understanding of the negative BOLD response from qualitative reasoning to a quantitative systems-biology level, which can be useful both in basic research and in clinical use.

  • 23.
    Tahmasebi, A.M.
    et al.
    Queen's University.
    Abolmaesumi, P.
    University of British Columbia.
    Wild, C,.
    Queen's University.
    Johnsrude, Ingrid
    Queen's University.
    A validation framework for probabilistic maps using Heschl's gyrus as a model.2010Ingår i: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 50, nr 2, s. 532-544Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Probabilistic maps are useful in functional neuroimaging research for anatomical labeling and for data analysis. The degree to which a probability map can accurately estimate the location of a structure of interest in a new individual depends on many factors, including variability in the morphology of the structure of interest over subjects, the registration (normalization procedure and template) applied to align the brains among individuals for constructing a probability map, and the registration used to map a new subject's data set to the frame of the probabilistic map. Here, we take Heschl's gyrus (HG) as our structure of interest, and explore the impact of different registration methods on the accuracy with which a probabilistic map of HG can approximate HG in a new individual. We assess and compare the goodness of fit of probability maps generated using five different registration techniques, as well as evaluating the goodness of fit of a previously published probabilistic map of HG generated using affine registration (Penhune et al., 1996). The five registration techniques are: three groupwise registration techniques (implicit reference-based or IRG, DARTEL, and BSpline-based); a high-dimensional pairwise registration (HAMMER) as well as a segmentation-based registration (unified segmentation of SPM5). The accuracy of the resulting maps in labeling HG was assessed using evidence-based diagnostic measures within a leave-one-out cross-validation framework. Our results demonstrated the out performance of IRG and DARTEL compared to other registration techniques in terms of sensitivity, specificity and positive predictive value (PPV). All the techniques displayed relatively low sensitivity rates, despite high PPV, indicating that the generated probability maps provide accurate but conservative estimates of the location and extent of HG in new individuals.

  • 24.
    Tahmasebi, Amir M.
    et al.
    Queen’s University, Kingston, ON, Canada.
    Abolmaesumi, Purang
    Queen’s University, Kingston, ON, Canada.
    Zheng, Zane Z.
    Queen’s University, Kingston, ON, Canada.
    Munhall, Kevin G.
    Queen’s University, Kingston, ON, Canada.
    Johnsrude, Ingrid
    Queen’s University, Kingston, ON, Canada.
    Reducing inter-subject anatomical variation: Effect of normalization method on sensitivity of functional magnetic resonance imaging data anaysis in auditory cortex and the superior temporal region.2009Ingår i: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 47, nr 4, s. 1522-1531Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Conventional group analysis of functional MRI (fMRI) data usually involves spatial alignment of anatomy across participants by registering every brain image to an anatomical reference image. Due to the high degree of inter-subject anatomical variability, a low-resolution average anatomical model is typically used as the target template, and/or smoothing kernels are applied to the fMRI data to increase the overlap among subjects’ image data. However, such smoothing can make it difficult to resolve small regions such as subregions of auditory cortex when anatomical morphology varies among subjects. Here, we use data from an auditory fMRI study to show that using a high-dimensional registration technique (HAMMER) results in an enhanced functional signal-to-noise ratio (fSNR) for functional data analysis within auditory regions, with more localized activation patterns. The technique is validated against DARTEL, a high-dimensional diffeomorphic registration, as well as against commonly used low-dimensional normalization techniques such as the techniques provided with SPM2 (cosine basis functions) and SPM5 (unified segmentation) software packages. We also systematically examine how spatial resolution of the template image and spatial smoothing of the functional data affect the results. Only the high-dimensional technique (HAMMER) appears to be able to capitalize on the excellent anatomical resolution of a single-subject reference template, and, as expected, smoothing increased fSNR, but at the cost of spatial resolution. In general, results demonstrate significant improvement in fSNR using HAMMER compared to analysis after normalization using DARTEL, or conventional normalization such as cosine basis function and unified segmentation in SPM, with more precisely localized activation foci, at least for activation in the region of auditory cortex.

  • 25.
    Tomo, Igor
    et al.
    arolinska Institutet and Karolinska University Hospital-Solna, Stockholm, Sweden.
    Le Calvez, Sophie
    arolinska Institutet and Karolinska University Hospital-Solna, Stockholm, Sweden.
    Maier, Hannes
    University of Hamburg, Germany.
    Boutet de Monvel, Jacques
    arolinska Institutet and Karolinska University Hospital-Solna, Stockholm, Sweden.
    Fridberger, Anders
    Karolinska Institutet and Karolinska University Hospital-Solna, Stockholm, Sweden.
    Ulfendahl, Mats
    arolinska Institutet and Karolinska University Hospital-Solna, Stockholm, Sweden.
    Imaging the living inner ear using intravital confocal microscopy2007Ingår i: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 35, nr 4, s. 1393-1400Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Confocal laser scanning microscopy permits detailed visualization of structures deep within thick fluorescently labeled specimen. This makes it possible to investigate living cells inside intact tissue without prior chemical sample fixation and sectioning. Isolated guinea pig temporal bones have previously been used for confocal experiments in vitro, but tissue deterioration limits their use to a few hours after the death of the animal. In order to preserve the cochlea in an optimal functional and physiological condition, we have developed an in vivo model based on a confocal microscopy approach. Using a ventral surgical approach, the inner ear is exposed in deeply anaesthetized, tracheotomized, living guinea pigs. To label the inner ear structures, scala tympani is perfused via an opening in the basal turn, delivering tissue culture medium with fluorescent vital dyes (RH 795 and calcein AM). An apical opening is made in the bony shell of cochlea to enable visualization using a custom-built objective lens. Intravital confocal microscopy, with preserved blood and nerve supply, may offer an important tool for studying auditory physiology and the pathology of hearing loss. After acoustic overstimulation, shortening and swelling of the sensory hair cells were observed.

  • 26.
    Westin, Carl-Fredrik
    et al.
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska fakulteten. Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
    Knutsson, Hans
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Tekniska fakulteten.
    Pasternak, Ofer
    Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
    Szczepankiewicz, Filip
    Department of Medical Radiation Physics, Lund University, Lund, Sweden.
    Özarslan, Evren
    Linköpings universitet, Institutionen för medicinsk teknik. Linköpings universitet, Tekniska fakulteten. Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Physics, Bogazici University, Istanbul, Turkey.
    van Westen, Danielle
    Department of Diagnostic Radiology, Lund University, Lund, Sweden.
    Mattisson, Cecilia
    Clinical Sciences, Psychiatry, Lund University, Lund, Sweden.
    Bogren, Mats
    Clinical Sciences, Psychiatry, Lund University, Lund, Sweden.
    O'Donnell, Lauren J
    Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
    Kubicki, Marek
    Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
    Topgaard, Daniel
    Division of Physical Chemistry, Department of Chemistry, Lund University, Lund, Sweden.
    Nilsson, Markus
    Lund University Bioimaging Center, Lund University, Lund, Sweden.
    Q-space trajectory imaging for multidimensional diffusion MRI of the human brain2016Ingår i: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 135, s. 345-362Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This work describes a new diffusion MR framework for imaging and modeling of microstructure that we call q-space trajectory imaging (QTI). The QTI framework consists of two parts: encoding and modeling. First we propose q-space trajectory encoding, which uses time-varying gradients to probe a trajectory in q-space, in contrast to traditional pulsed field gradient sequences that attempt to probe a point in q-space. Then we propose a microstructure model, the diffusion tensor distribution (DTD) model, which takes advantage of additional information provided by QTI to estimate a distributional model over diffusion tensors. We show that the QTI framework enables microstructure modeling that is not possible with the traditional pulsed gradient encoding as introduced by Stejskal and Tanner. In our analysis of QTI, we find that the well-known scalar b-value naturally extends to a tensor-valued entity, i.e., a diffusion measurement tensor, which we call the b-tensor. We show that b-tensors of rank 2 or 3 enable estimation of the mean and covariance of the DTD model in terms of a second order tensor (the diffusion tensor) and a fourth order tensor. The QTI framework has been designed to improve discrimination of the sizes, shapes, and orientations of diffusion microenvironments within tissue. We derive rotationally invariant scalar quantities describing intuitive microstructural features including size, shape, and orientation coherence measures. To demonstrate the feasibility of QTI on a clinical scanner, we performed a small pilot study comparing a group of five healthy controls with five patients with schizophrenia. The parameter maps derived from QTI were compared between the groups, and 9 out of the 14 parameters investigated showed differences between groups. The ability to measure and model the distribution of diffusion tensors, rather than a quantity that has already been averaged within a voxel, has the potential to provide a powerful paradigm for the study of complex tissue architecture.

  • 27.
    Wild, Conor J.
    et al.
    Queen's University, Kingston ON Canada.
    Davis, Matthew H.
    Medical Research Council Cognition and Brain Sciences Unit, Cambridge, UK.
    Johnsrude, Ingrid
    Linköpings universitet, Institutionen för beteendevetenskap och lärande, Handikappvetenskap. Linköpings universitet, Filosofiska fakulteten.
    Human auditory cortex is sensitive to the perceived clarity of speech2012Ingår i: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 60, nr 2, s. 1490-1502Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Feedback connections among auditory cortical regions may play an important functional role in processing naturalistic speech, which is typically considered a problem solved through serial feed-forward processing stages. Here, we used fMRI to investigate whether activity within primary auditory cortex (PAC) is sensitive to the perceived clarity of degraded sentences. A region-of-interest analysis using probabilistic cytoarchitectonic maps of PAC revealed a modulation of activity, in the most primary-like subregion (area Te1.0). related to the intelligibility of naturalistic speech stimuli that cannot be driven by stimulus differences. Importantly, this effect was unique to those conditions accompanied by a perceptual increase in clarity. Connectivity analyses suggested sources of input to PAC are higher-order temporal, frontal and motor regions. These findings are incompatible with feed-forward models of speech perception, and suggest that this problem belongs amongst modern perceptual frameworks in which the brain actively predicts sensory input, rather than just passively receiving it.

  • 28.
    Zekveld, Adriana
    et al.
    Linköpings universitet, Institutionen för beteendevetenskap och lärande, Handikappvetenskap. Linköpings universitet, Filosofiska fakulteten. Section Audiology, Dept. of Otolaryngology-Head and Neck Surgery and EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, Netherlands .
    Heslenfeld, D.J.
    Department of Psychology, VU University, BT Amsterdam, Netherlands.
    Johnsrude, Ingrid
    Linköpings universitet, Institutionen för beteendevetenskap och lärande, Handikappvetenskap. Linköpings universitet, Filosofiska fakulteten. Department of Psychology, Queen's University, Kingston, Canada; The School of Communication Sciences and Disorders and The Brain and Mind Institute, Natural Sciences Centre, Western University, London, Canada .
    Versfeld, N.J.
    Section Audiology, Dept. of Otolaryngology-Head and Neck Surgery and EMGO Institute for Health and Care Research, VU University of Medical Center, Amsterdam, Netherlands.
    Kramer, S.E.
    Section Audiology, Dept. of Otolaryngology-Head and Neck Surgery and EMGO Institute for Health and Care Research, VU University of Medical Center, Amsterdam, Netherlands.
    The eye as a window to the listening brain: Neural correlates of pupil size as a measure of cognitive listening load2014Ingår i: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 101, s. 76-86Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    An important aspect of hearing is the degree to which listeners have to deploy effort to understand speech. One promising measure of listening effort is task-evoked pupil dilation. Here, we use functional magnetic resonance imaging (fMRI) to identify the neural correlates of pupil dilation during comprehension of degraded spoken sentences in 17 normal-hearing listeners. Subjects listened to sentences degraded in three different ways: the target female speech was masked by fluctuating noise, by speech from a single male speaker, or the target speech was noise-vocoded. The degree of degradation was individually adapted such that 50% or 84% of the sentences were intelligible. Control conditions included clear speech in quiet, and silent trials.The peak pupil dilation was larger for the 50% compared to the 84% intelligibility condition, and largest for speech masked by the single-talker masker, followed by speech masked by fluctuating noise, and smallest for noise-vocoded speech. Activation in the bilateral superior temporal gyrus (STG) showed the same pattern, with most extensive activation for speech masked by the single-talker masker. Larger peak pupil dilation was associated with more activation in the bilateral STG, bilateral ventral and dorsal anterior cingulate cortex and several frontal brain areas. A subset of the temporal region sensitive to pupil dilation was also sensitive to speech intelligibility and degradation type. These results show that pupil dilation during speech perception in challenging conditions reflects both auditory and cognitive processes that are recruited to cope with degraded speech and the need to segregate target speech from interfering sounds. © 2014 Elsevier Inc.

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