Real-time motion analytics during brain MRI improve data quality and reduce costs

Head motion systematically distorts clinical and research MRI data. Motion artifacts have biased findings from many structural and functional brain MRI studies. An effective way to remove motion artifacts is to exclude MRI data frames affected by head motion. However, such post-hoc frame censoring can lead to data loss rates of 50% or more in our pediatric patient cohorts. Hence, many scanner operators collect additional 'buffer data', an expensive practice that, by itself, does not guarantee sufficient high-quality MRI data for a given participant. Therefore, we developed an easy-to-setup, easy-to-use Framewise Integrated Real-time MRI Monitoring (FIRMM) software suite that provides scanner operators with head motion analytics in real-time, allowing them to scan each subject until the desired amount of low-movement data has been collected. Our analyses show that using FIRMM to identify the ideal scan time for each person can reduce total brain MRI scan times and associated costs by 50% or more

Learning and comparing functional connectomes across subjects

Functional connectomes capture brain interactions via synchronized fluctuations in the functional magnetic resonance imaging signal. If measured during rest, they map the intrinsic functional architecture of the brain. With task-driven experiments they represent integration mechanisms between specialized brain areas. Analyzing their variability across subjects and conditions can reveal markers of brain pathologies and mechanisms underlying cognition. Methods of estimating functional connectomes from the imaging signal have undergone rapid developments and the literature is full of diverse strategies for comparing them. This review aims to clarify links across functional-connectivity methods as well as to expose different steps to perform a group study of functional connectomes

Does higher sampling rate (multiband + SENSE) improve group statistics - An example from social neuroscience block design at 3T

Multiband (MB) or Simultaneous multi-slice (SMS) acquisition schemes allow the acquisition of MRI signals from more than one spatial coordinate at a time. Commercial availability has brought this technique within the reach of many neuroscientists and psychologists. Most early evaluation of the performance of MB acquisition employed resting state fMRI or the most basic tasks. In this study, we tested whether the advantages of using MB acquisition schemes generalize to group analyses using a cognitive task more representative of typical cognitive neuroscience applications. Twenty-three subjects were scanned on a Philips 3 ​T scanner using five sequences, up to eight-fold acceleration with MB-factors 1 to 4, SENSE factors up to 2 and corresponding TRs of 2.45s down to 0.63s, while they viewed (i) movie blocks showing complex actions with hand object interactions and (ii) control movie blocks without hand object interaction. Data were processed using a widely used analysis pipeline implemented in SPM12 including the unified segmentation and canonical HRF modelling. Using random effects group-level, voxel-wise analysis we found that all sequences were able to detect the basic action observation network known to be recruited by our task. The highest t-values were found for sequences with MB4 acceleration. For the MB1 sequence, a 50% bigger voxel volume was needed to reach comparable t-statistics. The group-level t-values for resting state networks (RSNs) were also highest for MB4 sequences. Here the MB1 sequence with larger voxel size did not perform comparable to the MB4 sequence. Altogether, we can thus recommend the use of MB4 (and SENSE 1.5 or 2) on a Philips scanner when aiming to perform group-level analyses using cognitive block design fMRI tasks and voxel sizes in the range of cortical thickness (e.g. 2.7 ​mm isotropic). While results will not be dramatically changed by the use of multiband, our results suggest that MB will bring a moderate but significant benefit

Auditory feedback control mechanisms do not contribute to cortical hyperactivity within the voice production network in adductor spasmodic dysphonia

Adductor spasmodic dysphonia (ADSD), the most common form of spasmodic dysphonia, is a debilitating voice disorder characterized by hyperactivity and muscle spasms in the vocal folds during speech. Prior neuroimaging studies have noted excessive brain activity during speech in ADSD participants compared to controls. Speech involves an auditory feedback control mechanism that generates motor commands aimed at eliminating disparities between desired and actual auditory signals. Thus, excessive neural activity in ADSD during speech may reflect, at least in part, increased engagement of the auditory feedback control mechanism as it attempts to correct vocal production errors detected through audition. To test this possibility, functional magnetic resonance imaging was used to identify differences between ADSD participants and age-matched controls in (i) brain activity when producing speech under different auditory feedback conditions, and (ii) resting state functional connectivity within the cortical network responsible for vocalization. The ADSD group had significantly higher activity than the control group during speech (compared to a silent baseline task) in three left-hemisphere cortical regions: ventral Rolandic (sensorimotor) cortex, anterior planum temporale, and posterior superior temporal gyrus/planum temporale. This was true for speech while auditory feedback was masked with noise as well as for speech with normal auditory feedback, indicating that the excess activity was not the result of auditory feedback control mechanisms attempting to correct for perceived voicing errors in ADSD. Furthermore, the ADSD group had significantly higher resting state functional connectivity between sensorimotor and auditory cortical regions within the left hemisphere as well as between the left and right hemispheres, consistent with the view that excessive motor activity frequently co-occurs with increased auditory cortical activity in individuals with ADSD.First author draf

State and trait characteristics of anterior insula time-varying functional connectivity.

The human anterior insula (aINS) is a topographically organized brain region, in which ventral portions contribute to socio-emotional function through limbic and autonomic connections, whereas the dorsal aINS contributes to cognitive processes through frontal and parietal connections. Open questions remain, however, regarding how aINS connectivity varies over time. We implemented a novel approach combining seed-to-whole-brain sliding-window functional connectivity MRI and k-means clustering to assess time-varying functional connectivity of aINS subregions. We studied three independent large samples of healthy participants and longitudinal datasets to assess inter- and intra-subject stability, and related aINS time-varying functional connectivity profiles to dispositional empathy. We identified four robust aINS time-varying functional connectivity modes that displayed both "state" and "trait" characteristics: while modes featuring connectivity to sensory regions were modulated by eye closure, modes featuring connectivity to higher cognitive and emotional processing regions were stable over time and related to empathy measures

Disrupted functional brain network organization in patients with obstructive sleep apnea.

IntroductionObstructive sleep apnea (OSA) subjects show impaired autonomic, affective, executive, sensorimotor, and cognitive functions. Brain injury in OSA subjects appears in multiple sites regulating these functions, but the integrity of functional networks within the regulatory sites remains unclear. Our aim was to examine the functional interactions and the complex network organization of these interactions across the whole brain in OSA, using regional functional connectivity (FC) and brain network topological properties.MethodsWe collected resting-state functional magnetic resonance imaging (MRI) data, using a 3.0-Tesla MRI scanner, from 69 newly diagnosed, treatment-naïve, moderate-to-severe OSA (age, 48.3 ± 9.2 years; body mass index, 31 ± 6.2 kg/m(2); apnea-hypopnea index (AHI), 35.6 ± 23.3 events/h) and 82 control subjects (47.6 ± 9.1 years; body mass index, 25.1 ± 3.5 kg/m(2)). Data were analyzed to examine FC in OSA over controls as interregional correlations and brain network topological properties.ResultsObstructive sleep apnea subjects showed significantly altered FC in the cerebellar, frontal, parietal, temporal, occipital, limbic, and basal ganglia regions (FDR, P < 0.05). Entire functional brain networks in OSA subjects showed significantly less efficient integration, and their regional topological properties of functional integration and specialization characteristics also showed declined trends in areas showing altered FC, an outcome which would interfere with brain network organization (P < 0.05; 10,000 permutations). Brain sites with abnormal topological properties in OSA showed significant relationships with AHI scores.ConclusionsOur findings suggest that the dysfunction extends to resting conditions, and the altered FC and impaired network organization may underlie the impaired responses in autonomic, cognitive, and sensorimotor functions. The outcomes likely result from the prominent structural changes in both axons and nuclear structures, which occur in the condition