fMRI Activation Maps Research Articles

Deep EEG source localization via EMD-based fMRI high spatial frequency.

Brain imaging with a high-spatiotemporal resolution is crucial for accurate brain-function mapping. Electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI) are two popular neuroimaging modalities with complementary features that record brain function with high temporal and spatial resolution, respectively. One popular non-invasive way to obtain data with both high spatial and temporal resolutions is to combine the fMRI activation map and EEG data to improve the spatial resolution of the EEG source localization. However, using the whole fMRI map may cause spurious results for the EEG source localization, especially for deep brain regions. Considering the head's conductivity, deep regions' sources with low activity are unlikely to be detected by the EEG electrodes at the scalp. In this study, we use fMRI's high spatial-frequency component to identify the local high-intensity activations that are most likely to be captured by the EEG. The 3D Empirical Mode Decomposition (3D-EMD), a data-driven method, is used to decompose the fMRI map into its spatial-frequency components. Different validation measurements for EEG source localization show improved performance for the EEG inverse-modeling informed by the fMRI's high-frequency spatial component compared to the fMRI-informed EEG source-localization methods. The level of improvement varies depending on the voxels' intensity and their distribution. Our experimental results also support this conclusion.

Functional MRI during tongue strength tasks before and after partial glossectomy: Insights into the cortical activation of tongue motor function.

Because the tongue is a midline structure, studies on the neural correlates of lateralized tongue function are challenging and remain limited. Patients with tongue cancer who undergo unilateral partial glossectomy may be a unique cohort to study tongue-associated cortical activation, particularly regarding brain hemispheric lateralization. This longitudinal functional magnetic resonance imaging (fMRI) study investigated cortical activation changes for three tongue tasks before and after left-sided partial glossectomy in patients with squamous cell carcinoma of the tongue. Seven patients with squamous cell carcinoma involving the left tongue who underwent fMRI before and 6months after unilateral partial glossectomy were studied. Post-surgical changes in laterality index (LI) values for tongue-associated precentral and postcentral gyri fMRI activation were calculated for the dry swallow, tongue press, and saliva sucking tasks. Group analysis fMRI activation maps were generated for each of the three tasks. There were significant differences in changes in LI values post-surgery between the tongue press (p < 0.005; median: +0.24), saliva sucking (-0.10), and dry swallow tasks (-0.16). Decreased contralateral activation (change in LI ≥+0.20) was observed post-surgery during tongue press in six of seven patients, but only in two patients during saliva sucking and one patient during dry swallow (p < 0.05). There was also increased activation in the supplementary motor area following surgery. Post-surgical fMRI changes following left-sided partial glossectomy may suggest task-specific sensitivities to cortical activation changes following unilateral tongue deficits that may reflect the impacts of surgery and adaptive responses to tongue impairment.

BAYESIAN FUNCTIONAL REGISTRATION OF FMRI ACTIVATION MAPS.

Functional magnetic resonance imaging (fMRI) has provided invaluable insight into our understanding of human behavior. However, large inter-individual differences in both brain anatomy and functional localization after anatomical alignment remain a major limitation in conducting group analyses and performing population level inference. This paper addresses this problem by developing and validating a new computational technique for reducing misalignment across individuals in functional brain systems by spatially transforming each subjects functional data to a common reference map. Our proposed Bayesian functional registration approach allows us to assess differences in brain function across subjects and individual differences in activation topology. It combines intensity-based and feature-based information into an integrated framework, and allows inference to be performed on the transformation via the posterior samples. We evaluate the method in a simulation study and apply it to data from a study of thermal pain. We find that the proposed approach provides increased sensitivity for group-level inference.

Super-resolution generative adversarial networks with static T2*WI-based subject-specific learning to improve spatial difference sensitivity in fMRI activation

The spatial resolution of fMRI is relatively poor and improvements are needed to indicate more specific locations for functional activities. Here, we propose a novel scheme, called Static T2*WI-based Subject-Specific Super Resolution fMRI (STSS-SRfMRI), to enhance the functional resolution, or ability to discriminate spatially adjacent but functionally different responses, of fMRI. The scheme is based on super-resolution generative adversarial networks (SRGAN) that utilize a T2*-weighted image (T2*WI) dataset as a training reference. The efficacy of the scheme was evaluated through comparison with the activation maps obtained from the raw unpreprocessed functional data (raw fMRI). MRI images were acquired from 30 healthy volunteers using a 3 Tesla scanner. The modified SRGAN reconstructs a high-resolution image series from the original low-resolution fMRI data. For quantitative comparison, several metrics were calculated for both the STSS-SRfMRI and the raw fMRI activation maps. The ability to distinguish between two different finger-tapping tasks was significantly higher [p = 0.00466] for the reconstructed STSS-SRfMRI images than for the raw fMRI images. The results indicate that the functional resolution of the STSS-SRfMRI scheme is superior, which suggests that the scheme is a potential solution to realizing higher functional resolution in fMRI images obtained using 3T MRI.

Diffuse optical reconstructions of functional near infrared spectroscopy data using maximum entropy on the mean

Functional near-infrared spectroscopy (fNIRS) measures the hemoglobin concentration changes associated with neuronal activity. Diffuse optical tomography (DOT) consists of reconstructing the optical density changes measured from scalp channels to the oxy-/deoxy-hemoglobin concentration changes within the cortical regions. In the present study, we adapted a nonlinear source localization method developed and validated in the context of Electro- and Magneto-Encephalography (EEG/MEG): the Maximum Entropy on the Mean (MEM), to solve the inverse problem of DOT reconstruction. We first introduced depth weighting strategy within the MEM framework for DOT reconstruction to avoid biasing the reconstruction results of DOT towards superficial regions. We also proposed a new initialization of the MEM model improving the temporal accuracy of the original MEM framework. To evaluate MEM performance and compare with widely used depth weighted Minimum Norm Estimate (MNE) inverse solution, we applied a realistic simulation scheme which contained 4000 simulations generated by 250 different seeds at different locations and 4 spatial extents ranging from 3 to 40text {cm}^2 along the cortical surface. Our results showed that overall MEM provided more accurate DOT reconstructions than MNE. Moreover, we found that MEM was remained particularly robust in low signal-to-noise ratio (SNR) conditions. The proposed method was further illustrated by comparing to functional Magnetic Resonance Imaging (fMRI) activation maps, on real data involving finger tapping tasks with two different montages. The results showed that MEM provided more accurate HbO and HbR reconstructions in spatial agreement with the main fMRI cluster, when compared to MNE.

MP22-03 COGNITIVE PERFORMANCE CORRELATES WITH BRAIN ACTIVATION IN WOMEN WITH URGENCY URINARY INCONTINENCE

You have accessJournal of UrologyImaging/Radiology: Uroradiology II (MP22)1 Sep 2021MP22-03 COGNITIVE PERFORMANCE CORRELATES WITH BRAIN ACTIVATION IN WOMEN WITH URGENCY URINARY INCONTINENCE Rachel High, Zhaoyue Shi, Jill M. Danford, Erin T. Bird, Thomas J. Kuehl, Christof Karmonik, and Rose Khavari Rachel HighRachel High More articles by this author , Zhaoyue ShiZhaoyue Shi More articles by this author , Jill M. DanfordJill M. Danford More articles by this author , Erin T. BirdErin T. Bird More articles by this author , Thomas J. KuehlThomas J. Kuehl More articles by this author , Christof KarmonikChristof Karmonik More articles by this author , and Rose KhavariRose Khavari More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002013.03AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: The prevalence of urgency urinary incontinence (UUI) and cognitive impairment increase with age. Some studies indicate UI may be an early symptom of ongoing neurodegeneration. Brain activation studies of healthy and cognitively impaired adults have found correlations between brain activation and cognitive performance. There are no studies to evaluate brain activation in women with UUI screened for cognitive impairment. This study examines whether clinical cognitive scores correlate with brain activation patterns in women with UUI not undergoing therapy. METHODS: This is an observational cohort study of functional MRI (fMRI) and cognitive and urinary clinical data from women with UUI and therapy naive. Women aged ≥50 years completed symptom questionnaires and a modified Auditory Verbal Learning test. Subjects with incomplete bladder emptying, moderate-severe depression or anxiety, screening assessment positive for cognitive impairment, and pelvic floor therapy or UUI medications within the last 6 months were excluded. Learning over trials (LOT), short term retention (STR), long term retention (LTR), recognition % correct (Rc%) scores which were scaled for age-correction were calculated. Data was transformed into MNI 152 space for whole brain voxel-wise analysis. A fMRI activation map was created from which areas of significant activation were identified (students t-test p<0.05). Correlation coefficients were calculated for the T-statistics of each region with cognitive scores. Significant (p<0.05) correlations were reported for each region & respective LOT, STR, LTR, and Rc% scores. RESULTS: Images were obtained in twelve women with a median (IQR) age of 64 (55,68) years. Bladder diaries showed median (IQR) daily: 10 (9,10) urgency episodes, 11 (9,12) voids, and 5 (3, 5) leaks with urgency. Activation of regions involved in memory encoding and retrieval, including the hippocampus, inversely correlated with multiple cognitive testing domains (Table). Activity in the insula, cingulate gyrus, and prefrontal cortex did not correlate with cognitive scores. CONCLUSIONS: In women with UUI, performance on learning, recall, and recognition tasks negatively correlates with activation in regions involved in episodic memory. Source of Funding: International Urogynecological Association Clinical Research Grant and Baylor Scott & White Health Department of Women's Health. Dr. Rose Khavari is partially supported by K23DK118209 through NIDDK © 2021 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 206Issue Supplement 3September 2021Page: e391-e391 Advertisement Copyright & Permissions© 2021 by American Urological Association Education and Research, Inc.MetricsAuthor Information Rachel High More articles by this author Zhaoyue Shi More articles by this author Jill M. Danford More articles by this author Erin T. Bird More articles by this author Thomas J. Kuehl More articles by this author Christof Karmonik More articles by this author Rose Khavari More articles by this author Expand All Advertisement Loading ...

Enhanced Fiber Tractography Using Edema Correction: Application and Evaluation in High-Grade Gliomas.

A limitation of diffusion tensor imaging (DTI)-based tractography is peritumoral edema that confounds traditional diffusion-based magnetic resonance metrics. To augment fiber-tracking through peritumoral regions by performing novel edema correction on clinically feasible DTI acquisitions and assess the accuracy of the fiber-tracks using intraoperative stimulation mapping (ISM), task-based functional magnetic resonance imaging (fMRI) activation maps, and postoperative follow-up as reference standards. Edema correction, using our bi-compartment free water modeling algorithm (FERNET), was performed on clinically acquired DTI data from a cohort of 10 patients presenting with suspected high-grade glioma and peritumoral edema in proximity to and/or infiltrating language or motor pathways. Deterministic fiber-tracking was then performed on the corrected and uncorrected DTI to identify tracts pertaining to the eloquent region involved (language or motor). Tracking results were compared visually and quantitatively using mean fiber count, voxel count, and mean fiber length. The tracts through the edematous region were verified based on overlay with the corresponding motor or language task-based fMRI activation maps and intraoperative ISM points, as well as at time points after surgery when peritumoral edema had subsided. Volume and number of fibers increased with application of edema correction; concordantly, mean fractional anisotropy decreased. Overlay with functional activation maps and ISM-verified eloquence of the increased fibers. Comparison with postsurgical follow-up scans with lower edema further confirmed the accuracy of the tracts. This method of edema correction can be applied to standard clinical DTI to improve visualization of motor and language tracts in patients with glioma-associated peritumoral edema.

EEG microstates are correlated with brain functional networks during slow-wave sleep

Electroencephalography (EEG) microstates have been extensively studied in wakefulness and have been described as the “atoms of thought”. Previous studies of EEG have found four microstates, i.e., microstates A, B, C and D, that are consistent among participants across the lifespan during the resting state. Studies using simultaneous EEG and functional magnetic resonance imaging (fMRI) have provided evidence for correlations between EEG microstates and fMRI networks during the resting state. Microstates have also been found during non-rapid eye movement (NREM) sleep. Slow-wave sleep (SWS) is considered the most restorative sleep stage and has been associated with the maintenance of sleep. However, the relationship between EEG microstates and brain functional networks during SWS has not yet been investigated. In this study, simultaneous EEG-fMRI data were collected during SWS to test the correspondence between EEG microstates and fMRI networks. EEG microstate-informed fMRI analysis revealed that three out of the four microstates showed significant correlations with fMRI data: 1) fMRI fluctuations in the insula and posterior temporal gyrus positively correlated with microstate B, 2) fMRI signals in the middle temporal gyrus and fusiform gyrus negatively correlated with microstate C, and 3) fMRI fluctuations in the occipital lobe negatively correlated with microstate D, while fMRI signals in the anterior cingulate and cingulate gyrus positively correlated with this microstate. Functional brain networks were then assessed using group independent component analysis based on the fMRI data. The group-level spatial correlation analysis showed that the fMRI auditory network overlapped the fMRI activation map of microstate B, the executive control network overlapped the fMRI deactivation of microstate C, and the visual and salience networks overlapped the fMRI deactivation and activation maps of microstate D. In addition, the subject-level spatial correlations between the general linear model (GLM) beta map of each microstate and the individual maps of each component yielded by dual regression also showed that EEG microstates were closely associated with brain functional networks measured using fMRI during SWS. Overall, the results showed that EEG microstates were closely related to brain functional networks during SWS, which suggested that EEG microstates provide an important electrophysiological basis underlying brain functional networks.

Orthonasal versus retronasal glomerular activity in rat olfactory bulb by fMRI

Odorants can reach olfactory receptor neurons (ORNs) by two routes: orthonasally, when volatiles enter the nasal cavity during inhalation/sniffing, and retronasally, when food volatiles released in the mouth pass into the nasal cavity during exhalation/eating. Previous work in humans has shown that both delivery routes of the same odorant can evoke distinct perceptions and patterns of neural responses in the brain. Each delivery route is known to influence specific responses across the dorsal region of the glomerular sheet in the olfactory bulb (OB), but spatial distributions across the entire glomerular sheet throughout the whole OB remain largely unexplored. We used functional MRI (fMRI) to measure and compare activations across the entire glomerular sheet in rat OB resulting from both orthonasal and retronasal stimulations of the same odors. We observed reproducible fMRI activation maps of the whole OB during both orthonasal and retronasal stimuli. However, retronasal stimuli required double the orthonasal odor concentration for similar response amplitudes. Regardless, both the magnitude and spatial extent of activity were larger during orthonasal versus retronasal stimuli for the same odor. Orthonasal and retronasal response patterns show overlap as well as some route-specific dominance. Orthonasal maps were dominant in dorsal-medial regions, whereas retronasal maps were dominant in caudal and lateral regions. These different whole OB encodings likely underlie differences in odor perception between these biologically important routes for odorants among mammals. These results establish the relationships between orthonasal and retronasal odor representations in the rat OB.

Brain activation patterns of female multiple sclerosis patients with voiding dysfunction.

We compared brain activation patterns between female multiple sclerosis (MS) patients with voiding dysfunction (VD) and those without. We aim to expand current knowledge of supraspinal correlates of voiding initiation within a cohort of female MS patients with and without VD. Twenty-eight ambulatory female MS patients with stable disease and lower urinary tract dysfunction were recruited for this study. Subjects were divided into group 1, without VD (n = 14), and group 2, with VD (n = 14), defined as postvoid residual urine of ≥40% of maximum cystometric capacity or need for self-catheterization. We recorded brain activity via functional magnetic resonance imaging (fMRI) with simultaneous urodynamic testing. Average fMRI activation maps (the Student t test) were created for both groups, and areas of significant activation were identified (P < .05). A priori regions of interest (ROIs), identified by prior meta-analysis to be involved in voiding, were selected. Group-averaged blood-oxygen level-dependent (BOLD) activation maps demonstrated significant differences between groups 1 and 2 during initiation of voiding with group 2 showing significantly lower levels of activation in all ROIs except for the left cerebellum and right cingulate gyrus. Interestingly, group 2 displayed negative BOLD signals, while group 1 displayed positive signals in the right and left pontine micturition center, right periaqueductal gray, left thalamus, and left cingulate gyrus. The activation map of group 1 was similar to healthy controls. Our results support the hypothesis that distinct supraspinal activation patterns exist between female MS patients with VD and those without.

Imaging brain function with simultaneous BOLD and viscoelasticity contrast: fMRI/fMRE

Magnetic resonance elastography (MRE) is emerging as a new tool for studying viscoelastic changes in the brain resulting from functional processes. Here, we demonstrate a novel time series method to generate robust functional magnetic resonance elastography (fMRE) activation maps in response to a visual task with a flashing checkerboard stimulus. Using a single-shot spin-echo (SS-SE) pulse sequence, the underlying raw images inherently contain blood-oxygen-level dependent (BOLD) contrast, allowing simultaneous generation of functional magnetic resonance imaging (fMRI) activation maps from the magnitude and functional magnetic resonance elastography (fMRE) maps from the phase. This allows an accurate comparison of the spatially localized stiffness (fMRE) and BOLD (fMRI) changes within a single scan, eliminating confounds inherent in separately acquired scans. Results indicate that tissue stiffness within the visual cortex increases 6–11% with visual stimuli, whereas the BOLD signal change was 1–2%. Furthermore, the fMRE and fMRI activation maps have strong spatial overlap within the visual cortex, providing convincing evidence that fMRE is possible in the brain. However, the fMRE temporal SNR (tSNRfMRE) maps are heterogeneous across the brain. Using a dictionary matching approach to characterize the time series, the viscoelastic changes are consistent with a viscoelastic response function (VRF) time constant of 12.1 ​s ± 3.0 ​s for a first-order exponential decay, or a shape parameter of 8.1 ​s ± 1.4 ​s for a gamma-variate.

Data-Driven Machine-Learning Quantifies Differences in the Voiding Initiation Network in Neurogenic Voiding Dysfunction in Women With Multiple Sclerosis.

PurposeTo quantify the relative importance of brain regions responsible for reduced functional connectivity (FC) in their Voiding Initiation Network in female multiple sclerosis (MS) patients with neurogenic lower urinary tract dysfunction (NLUTD) and voiding dysfunction (VD). A data-driven machine-learning approach is utilized for quantification.MethodsTwenty-seven ambulatory female patients with MS and NLUTD (group 1: voiders, n=15 and group 2: VD, n=12) participated in a functional magnetic resonance imaging (fMRI) voiding study. Brain activity was recorded by fMRI with simultaneous urodynamic testing. The Voiding Initiation Network was identified from averaged fMRI activation maps. Four machine-learning algorithms were employed to optimize the area under curve (AUC) of the receiver-operating characteristic curve. The optimal model was used to identify the relative importance of relevant brain regions.ResultsThe Voiding Initiation Network exhibited stronger FC for voiders in frontal regions and stronger disassociation in cerebellar regions. Highest AUC values were obtained with ‘random forests’ (0.86) and ‘partial least squares’ algorithms (0.89). While brain regions with highest relative importance (>75%) included superior, middle, inferior frontal and cingulate regions, relative importance was larger than 60% for 186 of the 227 brain regions of the Voiding Initiation Network, indicating a global effect.ConclusionsVoiders and VD patients showed distinctly different FC in their Voiding Initiation Network. Machine-learning is able to identify brain centers contributing to these observed differences. Knowledge of these centers and their connectivity may allow phenotyping patients to centrally focused treatments such as cortical modulation.

Similarity of functional connectivity patterns in patients with multiple sclerosis who void spontaneously versus patients with voiding dysfunction.

To investigate if Multiple Sclerosis (MS) lesion characteristics affect functional brain connectivity (FC) during bladder voiding. Twenty-seven ambulatory female patients with MS completed our functional magnetic resonance imaging (fMRI)/urodynamic testing (UDS) platform. Individual fMRI activation maps were generated at initiation of voiding. FC patterns of these regions were calculated and compared. Similarity of the FC pattern from one patient relative to all others was expressed by a parameter FC_sim. A statistical analysis was performed to reveal the relationship of the existence of an enhancing brain lesion, the size of the largest lesion and the ability to void spontaneously to this FC similarity measure. FC_sim values were significantly lower for patients with an enhancing MS lesion (11.7 ± 3.1 vs 5.3 ± 2.1 P < 0.001). Lesion size smaller than 20 mm inversely correlated significantly with FC_sim (R = -0.43, P = 0.05). Patients with the ability to void spontaneously had a higher FC_sim value (12.0 ± 2.8 vs 9.3 ± 4.4 s, P = 0.08). Patients that exhibited a decrease of compliance also showed a significantly lower FC_sim value (11.3 ± 3.5 vs 4.7 ± 0.7, P < 1e-5). FC connectivity analysis derived from an fMRI task-based study including repetitive voiding cycles is able to quantify the heterogeneity of connectivity patterns in the brain of MS patients. FC similarity decreased with maximum lesion size or the presence of enhancing lesions affecting the ability to void spontaneously.

P28. The functional role of the anterior intraparietal sulcus for recovery of hand function in chronic stroke patients – A combined fMRI-TMS study

Introduction After stroke, neuroimaging studies frequently show increased activation of contralesional regions such as the primary motor cortex (M1) and the anterior intraparietal sulcus (aIPS) during movements of the impaired hand ( Rehme et al., 2012 ). There is evidence that these areas may adopt either supportive or disturbing implications for motor control, depending on multiple factors, such as age, stroke severity, and lesion location ( Di Pino et al., 2014 ). Importantly, previous research has mainly focused on investigating this question in the contralesional M1, while other areas involved in motor control, such as the aIPS have often been neglected despite considerable changes in post-stroke activity. Hence, we here examined the role of both ipsi- and contralesional aIPS for recovered motor function in the chronic phase post stroke using neuronavigated ‘online-TMS’ guided by individual fMRI activation maps. Methods First, we assessed structural and functional MRI data of chronic stroke patients and age-matched controls. During fMRI, participants performed an index finger tapping task to localize motor-related activation. The coordinates of peak activity in bilateral aIPS were identified in each participant and subsequently used as stimulation targets to apply short trains of rTMS (10 Hz trains, 90% of resting motor threshold, rMT) time locked to hand movements of different complexity: Participants performed (i) index finger tapping, (ii) pointing between two targets, and (iii) reach-to-grasp movements while ipsilateral M1, aIPS, or contralateral aIPS were transiently disturbed by rTMS. Sham stimulation served as control with the coil being tilted over the parieto-occipital vertex. Task performance was measured using a 3D motion analysis system (Zebris). Results TMS interference with aIPS contralateral to the moving hand led to altered kinematics across all tasks modulating finger tapping amplitudes, pointing accuracy and maximum grip aperture during grasping, highlighting the role of this region for hand motor control in patients and healthy controls. In contrast, interference with aIPS and M1 ipsilateral to the moving hand revealed differential effects in patients. Preliminary data suggest distinct roles of these contralesional areas for recovered hand function in chronic stroke. Conclusions The present findings provide proof-of-principle for the use of fMRI-guided TMS allowing to assess target regions’ functions for hand motor control on the single-subject level. Implementing this approach in a larger cohort of stroke patients provides a promising strategy to individually characterize maladaptive or supportive roles in bilateral aIPS and the contralesional M1 in relation to patient’s motor impairment and lesion topology.

Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging

Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are two of the fundamental noninvasive methods for identifying brain activity. Multimodal methods have sought to combine the high temporal resolution of EEG with the spatial precision of fMRI, but the complexity of this approach is currently in need of improvement. The protocol presented here describes the recently developed spatiotemporal fMRI-constrained EEG source imaging method, which seeks to rectify source biases and improve EEG-fMRI source localization through the dynamic recruitment of fMRI sub-regions. The process begins with the collection of multimodal data from concurrent EEG and fMRI scans, the generation of 3D cortical models, and independent EEG and fMRI processing. The processed fMRI activation maps are then split into multiple priors, according to their location and surrounding area. These are taken as priors in a two-level hierarchical Bayesian algorithm for EEG source localization. For each window of interest (defined by the operator), specific segments of the fMRI activation map will be identified as active to optimize a parameter known as model evidence. These will be used as soft constraints on the identified cortical activity, increasing the specificity of the multimodal imaging method by reducing cross-talk and avoiding erroneous activity in other conditionally active fMRI regions. The method generates cortical maps of activity and time-courses, which may be taken as final results, or used as a basis for further analyses (analyses of correlation, causation, etc.) While the method is somewhat limited by its modalities (it will not find EEG-invisible sources), it is broadly compatible with most major processing software, and is suitable for most neuroimaging studies.

Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging

Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are two of the fundamental noninvasive methods for identifying brain activity. Multimodal methods have sought to combine the high temporal resolution of EEG with the spatial precision of fMRI, but the complexity of this approach is currently in need of improvement. The protocol presented here describes the recently developed spatiotemporal fMRI-constrained EEG source imaging method, which seeks to rectify source biases and improve EEG-fMRI source localization through the dynamic recruitment of fMRI sub-regions. The process begins with the collection of multimodal data from concurrent EEG and fMRI scans, the generation of 3D cortical models, and independent EEG and fMRI processing. The processed fMRI activation maps are then split into multiple priors, according to their location and surrounding area. These are taken as priors in a two-level hierarchical Bayesian algorithm for EEG source localization. For each window of interest (defined by the operator), specific segments of the fMRI activation map will be identified as active to optimize a parameter known as model evidence. These will be used as soft constraints on the identified cortical activity, increasing the specificity of the multimodal imaging method by reducing cross-talk and avoiding erroneous activity in other conditionally active fMRI regions. The method generates cortical maps of activity and time-courses, which may be taken as final results, or used as a basis for further analyses (analyses of correlation, causation, etc.) While the method is somewhat limited by its modalities (it will not find EEG-invisible sources), it is broadly compatible with most major processing software, and is suitable for most neuroimaging studies.

Extremely preterm children exhibit increased interhemispheric connectivity for language: findings from fMRI‐constrained MEG analysis

Children born extremely preterm are at significant risk for cognitive impairment, including language deficits. The relationship between preterm birth and neurological changes that underlie cognitive deficits is poorly understood. We use a stories‐listening task in fMRI and MEG to characterize language network representation and connectivity in children born extremely preterm (n = 15, <28 weeks gestation, ages 4–6 years), and in a group of typically developing control participants (n = 15, term birth, 4–6 years). Participants completed a brief neuropsychological assessment. Conventional fMRI analyses revealed no significant differences in language network representation across groups (p > .05, corrected). The whole‐group fMRI activation map was parcellated to define the language network as a set of discrete nodes, and the timecourse of neuronal activity at each position was estimated using linearly constrained minimum variance beamformer in MEG. Virtual timecourses were subjected to connectivity and network‐based analyses. We observed significantly increased beta‐band functional connectivity in extremely preterm compared to controls (p < .05). Specifically, we observed an increase in connectivity between left and right perisylvian cortex. Subsequent effective connectivity analyses revealed that hyperconnectivity in preterms was due to significantly increased information flux originating from the right hemisphere (p < 0.05). The total strength and density of the language network were not related to language or nonverbal performance, suggesting that the observed hyperconnectivity is a “pure” effect of prematurity. Although our extremely preterm children exhibited typical language network architecture, we observed significantly altered network dynamics, indicating reliance on an alternative neural strategy for the language task.

PD04-01 CHANGES IN BRAIN ACTIVITY FOLLOWING INTRADETRUSOR INJECTION OF ONABOTULINUMTOXINA IN PATIENTS WITH MULTIPLE SCLEROSIS: AN FMRI STUDY

You have accessJournal of UrologyUrodynamics/Lower Urinary Tract Dysfunction/Female Pelvic Medicine: Neurogenic Voiding Dysfunction I1 Apr 2018PD04-01 CHANGES IN BRAIN ACTIVITY FOLLOWING INTRADETRUSOR INJECTION OF ONABOTULINUMTOXINA IN PATIENTS WITH MULTIPLE SCLEROSIS: AN FMRI STUDY Rose Khavari, Christof Karmonik, Saba Elias, and Timothy Boone Rose KhavariRose Khavari More articles by this author , Christof KarmonikChristof Karmonik More articles by this author , Saba EliasSaba Elias More articles by this author , and Timothy BooneTimothy Boone More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2018.02.279AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES OnabotulinumtoxinA (BTX-A) is a well-described treatment for Neurogenic Detrusor Overactivity (NDO) and while its motor effects on detrusor muscle is extensively studied, its sensory effects are not. Prior functional neuroimaging studies have suggested that women with overactive bladder have increased brain activity in the cingulate cortex, insula, and frontal cortex in response to bladder filling. The aim of this study was to evaluate the impact of intradetrusor BTX-A on brain activity in female multiple sclerosis (MS) patients with NDO using concurrent functional magnetic resonance imaging (fMRI) and UDS in a priori regions of interest. METHODS We conducted a prospective study of 12 women with stable MS and NDO undergoing fMRI with simultaneous UDS prior to and 6-weeks following BTX-A. During the filling phase patients signalled the strong urgency. From individual fMRI activation maps at strong urgency average fMRI activation map in MNI (Montreal Neuroimaging Institute) space were created for pre and post BTX-A from which areas of significant activation were identified (p<0.05). RESULTS fMRI activation increased post BTX-A in the right cingulate body (x (right positive),y (posterior positive),z (inferior positive) coordinates = 17,4,39, p=0.0012), ), the left posterior cingulate (-7,-37,22,p=0.02), the left anterior cingulate (-3,24,8,p=0.0015), the right prefrontal cortex (3,51,46,p=0.0015), the insula (32,12,14,p=0.0138) and the pons micturition center (3,-29,-28,p=0.05). Areas that showed decreased activity were sparse and included the left cerebellum (-31,-63,-62,p=0.001), the left fusiform gyrus (-40,-3,-28,p=0.065) and the bilateral lentiform nucleus (-17,6,-9 and 18,2,-9, p=0.026). CONCLUSIONS Intradetrusor injection of BTX-A appears to increase the activity of the brain regions known to be involved in sensation and process of urinary urgency in female MS patients with NDO. This is the first study of its kind to evaluate the possible sensory effects of BTX-A at the human brain level where sensory awareness is located. This pattern of activation may be used to phenotype patients further to optimize therapy or to uncover sensory effects of onabotulinumtoxinA beyond the bladder. © 2018FiguresReferencesRelatedDetails Volume 199Issue 4SApril 2018Page: e77 Advertisement Copyright & Permissions© 2018MetricsAuthor Information Rose Khavari More articles by this author Christof Karmonik More articles by this author Saba Elias More articles by this author Timothy Boone More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...

PD04-02 SUPRASPINAL CONTROL VARIAITONS IN MULTIPLE SCLEROSIS PATIENTS WHO VOID SPONTANOUSLY VERUS PATIENTS WITH VOIDING DYSFUNCTION

You have accessJournal of UrologyUrodynamics/Lower Urinary Tract Dysfunction/Female Pelvic Medicine: Neurogenic Voiding Dysfunction I1 Apr 2018PD04-02 SUPRASPINAL CONTROL VARIAITONS IN MULTIPLE SCLEROSIS PATIENTS WHO VOID SPONTANOUSLY VERUS PATIENTS WITH VOIDING DYSFUNCTION Rose Khavari, Christof Karmonik, and Timothy Boone Rose KhavariRose Khavari More articles by this author , Christof KarmonikChristof Karmonik More articles by this author , and Timothy BooneTimothy Boone More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2018.02.280AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES In this study, we seek to compare brain activity processes at the time of initiation of voiding in Multiple Sclerosis (MS) patients who are voiders versus patients with voiding dysfunction. We hypothesize that female MS patients with voiding dysfunction have a distinct Blood Oxygen Level Dependent (BOLD) pattern activation in specific a priori regions of interest (ROIs) at the time of initiation of voiding when compared to patients who void spontaneously. METHODS Twenty seven ambulatory female MS patients with lower urinary tract dysfunction were recruited for this IRB approved study: Group 1; voiders (n=15) and group 2; voiding dysfunction (n=12) which was defined as patients with postvoid residual urine of = 40% of their maximum cystometric capacity or patients who performed self-catheterization. We recorded brain activity via fMRI with simultaneous urodynamic testing (UDS). From the transformed datasets, average fMRI activation maps (student t-test) for both groups were created, and areas of significant activation were identified (p<0.05). A priori ROIs identified by a prior meta-analysis to be involved in voiding were selected. RESULTS Group-averaged BOLD activation maps indicated distinct differences in activation patterns between groups (figure 1a). A reversed (negative) BOLD effect was noted in the PMC, PAG, left cingulate, left thalamus and the reticular formation. Interpretation of results Earlier positron emission topography studies have identified right dorsomedial pontine tegmentum and the right inferior frontal gyrus to be associated with significantly increased blood flow in healthy women at the time of voiding. Our results are consistent with these preliminary data in the literature where PMC, PAG, left cingulate, left thalamus and the reticular formation seem to have different pattern of activation between female MS voiders and the ones with voiding dysfunction. CONCLUSIONS Our preliminary group and network analyses demonstrate that distinct supraspinal patterns of activation and deactivation exists between MS patients who are voiders and who have voiding dysfunction. © 2018FiguresReferencesRelatedDetails Volume 199Issue 4SApril 2018Page: e77-e78 Advertisement Copyright & Permissions© 2018MetricsAuthor Information Rose Khavari More articles by this author Christof Karmonik More articles by this author Timothy Boone More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...

3D spatially-adaptive canonical correlation analysis: Local and global methods

Local spatially-adaptive canonical correlation analysis (local CCA) with spatial constraints has been introduced to fMRI multivariate analysis for improved modeling of activation patterns. However, current algorithms require complicated spatial constraints that have only been applied to 2D local neighborhoods because the computational time would be exponentially increased if the same method is applied to 3D spatial neighborhoods.In this study, an efficient and accurate line search sequential quadratic programming (SQP) algorithm has been developed to efficiently solve the 3D local CCA problem with spatial constraints. In addition, a spatially-adaptive kernel CCA (KCCA) method is proposed to increase accuracy of fMRI activation maps. With oriented 3D spatial filters anisotropic shapes can be estimated during the KCCA analysis of fMRI time courses. These filters are orientation-adaptive leading to rotational invariance to better match arbitrary oriented fMRI activation patterns, resulting in improved sensitivity of activation detection while significantly reducing spatial blurring artifacts. The kernel method in its basic form does not require any spatial constraints and analyzes the whole-brain fMRI time series to construct an activation map. Finally, we have developed a penalized kernel CCA model that involves spatial low-pass filter constraints to increase the specificity of the method.The kernel CCA methods are compared with the standard univariate method and with two different local CCA methods that were solved by the SQP algorithm. Results show that SQP is the most efficient algorithm to solve the local constrained CCA problem, and the proposed kernel CCA methods outperformed univariate and local CCA methods in detecting activations for both simulated and real fMRI episodic memory data.