MNI Space Research Articles

Characterization of functional brain connectivity towards optimization of music selection for therapy: a fMRI study

Background: Music therapy, a nontraditional approach to patient care, has long been used to achieve a wide variety of positive results. To deepen our understanding of the connection and therapeutic potential of music, the effect of music therapy and music medicine (music administered to individuals without an interactive therapeutic relationship) on the brain remains a topic of active research.Objective: This study is aimed at investigating the effect of different music genres and individualized music selection on brain functional connectivity (FC) measured by functional magnetic resonance imaging (fMRI).Methods: Twelve healthy subjects listened to five excerpts: Bach with and without visual guide (unfamiliar), self-selected familiar music, Gagaku (unfamiliar music) and Chaplin (spoken word) while undergoing a block design fMRI study. fMRI datasets were imported into CONN (Matlab toolbox) and graph networks were created for 132 anatomical regions in MNI space. Group connectivity for each soundtrack was quantified and statistically analyzed using the R package.Results: Complex interactions between brain regions, cerebellar regions (713), superior frontal gyrus (178) and parahippocampus (223), were highest for self-selected music. Brain regions involving sound processing, memory retrieval, semantic processing and motor areas were continuously activated for all five excerpts; however, most connections were formed in language processing regions for the Bach excerpt.Conclusion: Functional brain connectivity varied by soundtrack with the largest degree of connectivity found consistently for self-selected and unfamiliar (Bach, Gagaku) music. Incorporating individualized music listening into existing therapy paradigms may positively contribute to standard protocol for stroke rehabilitation and prevention.

Practical Methods for Estimating Metabolic Flux (Ki) to Assess Response to Therapy via Static PET Scans.

320 Introduction: We have recently developed [18F]MNI-1126, as an 18F analog of the established [11C]UCB-J PET radioligand, for imaging synaptic vesicle glycoprotein 2A (SV2A). The tracer was previously tested in non-human primates, which demonstrated its specificity for SV2A as well as comparable imaging characteristics with [11C]UCB-J. We herein report a pilot study with [18F]MNI-1126 performed to further assess its in vivo characteristics in human brain, and to examine its capacity to measure differences in SV2A density between healthy subjects and those diagnosed with Parkinson disease (PD), and Alzheimer disease (AD). Methods: Brain PET imaging was performed in 11 human subjects, 4 HV (males, 53 ± 3 y), 4 PD (3 males, 1 female, 70 ± 7 y) and 3 AD (1 male, 2 females, 67 ± 10 y, MMSE 3,14 and 22). Dynamic image data were acquired for up to 180 min on a Siemens ECAT HR+ scanner following a 3 min bolus injection of [18F]MNI-1126 (297.7 ± 58.3 MBq). Arterial blood sampling with associated metabolite assays was acquired and enabled the generation of an arterial input function for kinetic modeling. Dynamic images were motion corrected and normalized into MNI space. Regions of interest were defined by Hammers, N30R83 atlas and intersected with gray and white matter segments. Regional brain time-activity curves (TACs) were generated and analyzed by one-tissue (1T), two-tissue (2T) compartment models, and Logan graphical analysis (LGA) to estimate regional volumes of distribution (VT). A binding potential (BPND) was estimated by assuming that the VT of centrum semiovale (CS) was reflective of the non-displaceable signal. Non-invasive LGA (NI-LGA) and simplified reference tissue model (SRTM), with CS as reference region were also explored. Time stability of both VT and BPND outcome measures was evaluated. Cross-sectional analysis of VT and BPND were performed across the healthy, PD and AD subject groups. Results: [18F]MNI-1126 readily entered the brain and its distribution was consistent with SV2A similar to [11C]UCB-J - high brain uptake (max SUV 9-12) reached at 15-30 min after injection, moderate washout, and high specific binding (max BPND ~5.0). Unmetabolized parent fraction was 52.4 ± 15.5 %, 24.9 ± 8.5 %, and 22.6 ± 7.3 %, at 15 min, 60 min, and 120 min post injection. Fraction of unbound tracer to plasma proteins (i.e., free fraction) was 32% ± 2%.VT and BPND estimates were relatively stable for scan durations of 40 min and 60 min, respectively (~5% different from 120 min). The 1T model produced better (lower AIC) and more reliable (low SE) fits than 2T. Across methods regional BPND computed with 1T model was highly correlated (R2~ 0.99) with LGA (no bias) and NI-LGA. NI-LGA estimates presented an increasing negative bias with BPND (slope ~0.85). Lower global VT (6%, 14%) and BPND (20%, 29%) were found in PD and AD subjects, respectively, compared to HV. In AD, the largest reductions in BPND were found in hippocampus (51%), and superior lateral temporal cortex (39%). These results indicate that reductions in SV2A density in AD can be measured in brain regions besides hippocampus, which have been previously reported with [11C]UCB-J. In PD, the largest reductions in BPND were found in caudate nucleus (38%), hippocampus (33%), and thalamus (30%). Conclusions: These first-in-human studies with [18F]MNI-1126 have confirmed its favorable in vivo imaging properties. Disease specific decreases in regional SV2A density were detected and quantified in both PD and AD subjects. These encouraging proof-of-concept data provide a rationale for future multicenter clinical trials to validate the utility of SV2A PET imaging in AD, PD and other neurodegenerative disorders.

Paragrammatism and agrammatism: a cortical double dissociation revealed by lesion-symptom mapping

Paragrammatism and agrammatism: a cortical double dissociation revealed by lesion-symptom mapping

SU17 - ALTERED BRAIN CONNECTIVITY IN PATIENTS WITH 16P11.2

Background Copy Number Variants (CNVs) at the 16p11.2 BP4-BP5 locus are among the most common genetic risk factors associated with neurodevelopmental disorders [1]. Deletion (DEL) have been associated with Autism Spectrum Disorder (ASD) and Duplication (DUP) with Schizophrenia and ASD. Voxel-based morphometry studies have revealed a robust association between the number of 16p11.2 genomic copies and global brain volume, as well as regional structural changes in key areas of the reward system, language circuitry and social cognition [2]. Our goal is to examine the effect of 16p11.2 CNVs on functional brain organization and its relationship with alterations in brain structure. Methods This study was conducted in a cohort of 20 16p11.2 DEL carriers, 19 DUP carriers and 74 controls (CON) [3]. Mean age was 23.8 yrs±14.9. Resting-state fMRI and structural scans were acquired at two sites on Siemens 3 T TIM Trio scanners using the same sequences (EPI: TR=3000; TE=30; scan time=06:12, flip angle=90). fMRI data were corrected for slice timing and subject motion and registered to MNI space [4] using the NIAK pipeline [5]. Timepoints with excessive head-motion (> 0.5mm) were removed [6]. Subjects with low time points ( Pairwise functional connectivity was estimated as the correlation between the average time series of 64 brain regions [7]. We then fitted a linear model to each connection with the CNV status, subject motion, sex and recording site as explanatory factors. Differences between CNV status groups were then tested by post-hoc contrasts. Each contrast was controlled for false discovery rate (FDR) across all connections at q Results Connectivity of regions in the basal ganglia, medial temporal gyrus and precuneus showed significant differences for the DEL vs CON, and DEL vs DUP contrasts. Specifically, connections among basal ganglia regions (caudate, thalamus, putamen) and between basal ganglia regions and superior and inferior temporal gyri showed significant overconnectivity in DEL group compared to both CON and DUP. Finally, connections between the caudate, superior frontal gyrus and inferior parietal lobule were found to be stronger in DEL than DUP. No significant differences of functional connectivity were found for the DUP vs CON contrast. We examined in a larger normative dataset whether changes in global brain volumes may mediate these changes but found no relationship between brain volume and connections altered in deletion carriers. Discussion Our results are concordant with previous findings of structural brain alterations in 16p11.2 DEL carriers. Striato-striatal and striato-cortical over-connectivity in the DEL carriers is consistent with previous reports of aberrant functional connectivity in ASD [10]. As previously observed the effect size of the duplication on brain structure and cognitive traits is smaller than the effects of the deletion. A larger sample size is likely required to observe the changes in connectivity associated with the duplication. 1. 10.1038/nature13908 2. 10.1038/mp.2014.145 3. 10.1016/j.neuron.2012.02.014 4. 10.1016/j.neuroimage.2010.07.033 5. niak.simexp-lab.org 6. 10.1016/j.neuroimage.2011.10.018 7. 10.6084/m9.figshare.1285615 8. www.jstor.org/stable/2346101 9. 10.1016/j.neuroimage.2015.07.071 10. 10.1016/j.biopsych.2010.10.029

Autonomic dysfunction and white matter microstructural changes in drug-naïve patients with Parkinson's disease.

BackgroundAutonomic dysfunction (AD) is one of the non-motor features of Parkinson’s disease (PD). Some symptoms tend to occur in the early stages of PD. AD also has a great impact on patient’s quality of life. In this study, we aimed to discover the association between AD (Scales for Outcomes in Parkinson’s disease-Autonomic, SCOPA-AUT) and microstructural changes in white matter tracts in drug-naïve early PD patients to elucidate the central effects of autonomic nervous system impairments.MethodIn total, this study included 85 subjects with PD recruited from the Parkinson’s Progression Markers Initiative (PPMI) database. Among the 85 PD patients, 38 were in Hoehn & Yahr stage 1 (HY1PD) and 47 were in stage 2 (HY2PD). Diffusion magnetic resonance imaging (DMRI) data were reconstructed in the MNI space using q-space diffeomorphic reconstruction to obtain the spin distribution function. The spin distribution function (SDF) values were used in DMRI connectometry analysis. We investigated through diffusion MRI connectometry the structural correlates of white matter tracts with SCOPA-AUT subscores and total score.ResultsConnectometry analysis also revealed positive association with white matter density in bilateral corticospinal tract in HY1PD patients and negative association in genu of corpus callosum (CC) and, bilateral cingulum in both groups. In addition, there were associations between gastrointestinal, sexual, thermoregulatory and urinary items and structural brain connectivity in PD.ConclusionOur study reveals positive correlation, suggesting neural compensations in early PD. Cingulum and CC tracts have well-known roles in PD pathology, compatible with our findings that bring new insights to specific areas of AD and its role in central nervous system (CNS) neurodegeneration, paving the way for using prodromal makers in the diagnosis and treatment of PD.

DIFFUSION-KURTOSIS IMAGING IN ASSESMENT OF BRAIN MICROSTRUCTURE. HEALTHY VOLUNTEERS MEASURMENTS

Aim:discover quantitative and qualitative variance of diffusion parameters in white and gray matter of healthyvolunteers brain. Discover correlation between diffusion and kurtosis parameters, find out if there is correlation between the parameters and aging microstructural changes.Materials and methods.14 healthy volunteers were investigated (9 men, 5 women; age from 21 to 55 years, mean 34). The volunteers were classified into two groups by age: 7 subjects who younger 35 (6 men and 1 woman, mean age 25) and 7 subjects who older 35 years (3 men and 4 women, mean age 44). We used 3.0 Tesla MRI (3.0T SignaHDxt, General Electric, USA) with 8 channel head coil, gradient strength 50 mT/m, slew rate 150 T/m/s. Diffusion imaging was based on echo planar “spin echo” sequence (SE EPI), TR = 10000 ms, TEmin = 102 ms, FOV = 240 mm, voxel size 3 × 3 × 3 mm3, 60 non-coplanar diffusion directions and three b-values: 0, 1000, 2500 s/mm2. Acquisition time of diffusion kurtosis imaging was 22 minutes. We excluded extracerebral areas on diffusion and kurtosis parametric maps using semi-automatic approach. After that, brain images were transformed to MNI152 space using affine method. Masks of 9 anatomical structures were applied to the transformed images. Diffusion and kurtosis values were measured in these structures.Results.Fractional anisotropy (FA) changed from 0.06 in lateral occipital cortex to 0.25 in cerebral white matter, kurtosis anisotropy (KA) changed from 0.03 to 0.14 in the same cerebral structures. Axial (AK), radial (RK) and mean kurtosis (MK) were minimal in superior frontal gyrus and maximal in cerebral white matter. AK changed from 0.55 to 0.72, RK changed from 0.62 to 1.05, MK from 0.59 to 0.88. Axial(AxEAD) and radial extra axonal water diffusion (RadEAD) were minimal in putamen and maximal in superior frontal gyrus. AxEAD was changing from 1.38 • 10–3 to 2.57 • 10–3, RadEAD from 1.03 • 10–3 to 2.34 • 10–3. Axonal water fraction (AWF) had minimal value 0,18 in superior frontal gyrus and maximal value 0.29 in cerebral white matter. Tortuosity (TORT) changed from 1.06 in lateral occipital cortex to 1.43 in cerebral white matter. There was significant difference between age groups in AWF, RK, RadEAD in putamen and in KA in superior temporal gyrus. Maximal correlation with age was in MK in superior temporal gyrus, anterior division. It was equal to 0.562.Conclusions:Diffusion kurtosis imaging is highly sensitive method of brain tissue microstructure assessment, which detects age-related changes.

P6. Toward optimized nonlinear deformation algorithms for subcortical DBS target regions in human brain MRI

Objective 1. To evaluate and optimize commonly used nonlinear deformation algorithms when applied to human brain MRI. 2. To evaluate and optimize accuracy of automated atlas-based segmentation of the two most commonly used target regions for deep brain stimulation (DBS), the nucleus subthalamicus (STN) and the internal part of the globus pallidus (GPi). 3. To guide clinicians as to which preoperative MRI sequences to acquire in patients undergoing DBS. Background Translating single-subject imaging into a common reference frame such as the MNI space is a ‘core concept within the field of brain mapping’ (Evans et al., 2012) making an accurate transformation into this space necessary. Here, we evaluated and optimized 6 commonly used deformation algorithms and compared each outcome to manually labeled brain regions of 103 brains. Methods Algorithms evaluated were: New Segment, DARTEL and SHOOT (SPM); FNIRT (FSL); SyN and BSpline (ANTs). Target space was the MNI 2009b NLIN space. An atlas of the STN and GPi in MNI space (Ewert et al., 2017) was transformed to native space by inverting each deformation matrix. The resulting atlas-based segmentations were then compared to expert manual segmentations of the native brains. Overlap between the two was quantified using the Dice coefficient (Dice et al., 1945), mean surface distance and correlation of volumes. Two open source datasets were used: The IXI-dataset ( http://www.brain-development.org/ixi-dataset/ ) and the HCP-dataset ( http://www.humanconnectomeproject.org/ ). Results The best performing algorithms were New Segment with a custom tissue probability map (TPM) (1) and ANTs SyN (2) with an additional step to refine subcortical coregistration. Performance is compared to inter-rater results (3) of manual segmentations. Fig. 1 shows results for the HCP data for STN (L, in red) and GPi (R, in blue) separately: median Dice for STN (1): 0.70 (std: 0.1); (2): 0.72 (0.06); (3): 0.76 (0.09). Median of mean surface distance in mm for STN: (1): 0.45 (0.14); (2): 0.38 (0.07); (3): 0.41 (0.2). Correlation between automated and manual volumes are for (1) R = 0.296, p . Conclusion First, we identified two nonlinear deformation algorithms that perform superiorly to other commonly used algorithms in the field. We then further optimized their performance resulting in a more precise alignment of subcortical structures. The results of atlas-based segmentations are similar to inter-rater results made by expert manual raters. Second, multimodal image registration was more accurate than unimodal image registration. We conclude that preoperative imaging of DBS patients should include at least a T1- and T2-weighted modality.

Differential Age-Related Changes in Structural Covariance Networks of Human Anterior and Posterior Hippocampus.

The hippocampus plays an important role in memory function relying on information interaction between distributed brain areas. The hippocampus can be divided into the anterior and posterior sections with different structure and function along its long axis. The aim of this study is to investigate the effects of normal aging on the structural covariance of the anterior hippocampus (aHPC) and the posterior hippocampus (pHPC). In this study, 240 healthy subjects aged 18–89 years were selected and subdivided into young (18–23 years), middle-aged (30–58 years), and older (61–89 years) groups. The aHPC and pHPC was divided based on the location of uncal apex in the MNI space. Then, the structural covariance networks were constructed by examining their covariance in gray matter volumes with other brain regions. Finally, the influence of age on the structural covariance of these hippocampal sections was explored. We found that the aHPC and pHPC had different structural covariance patterns, but both of them were associated with the medial temporal lobe and insula. Moreover, both increased and decreased covariances were found with the aHPC but only increased covariance was found with the pHPC with age (p < 0.05, family-wise error corrected). These decreased connections occurred within the default mode network, while the increased connectivity mainly occurred in other memory systems that differ from the hippocampus. This study reveals different age-related influence on the structural networks of the aHPC and pHPC, providing an essential insight into the mechanisms of the hippocampus in normal aging.

In-vivo quantitative structural imaging of the human midbrain and the superior colliculus at 9.4T

We explored anatomical details of the superior colliculus (SC) by in vivo magnetic resonance imaging (MRI) at 9.4T. The high signal-to-noise ratio allowed the acquisition of high resolution, multi-modal images with voxel sizes ranging between 176 × 132 × 600 μm and (800)3μm. Quantitative mapping of the longitudinal relaxation rate R1, the effective transverse relaxation rate R2*, and the magnetic susceptibility QSM was performed in 14 healthy volunteers. The images were analyzed in native space as well as after normalization to a common brain space (MNI). The coefficient-of-variation (CoV) across subjects was evaluated in prominent regions of the midbrain, reaching the best reproducibility (CoV of 5%) in the R2* maps of the SC in MNI space, while the CoV in the QSM maps remained high regardless of brain-space. To investigate whether more complex neurobiological architectural features could be detected, depth profiles through the SC layers towards the red nucleus (RN) were evaluated at different levels of the SC along the rostro-caudal axis. This analysis revealed alterations of the quantitative MRI parameters concordant with previous post mortem histology studies of the cyto- and myeloarchitecture of the SC. In general, the R1 maps were hyperintense in areas characterized by the presence of abundant myelinated fibers, and likely enabled detection of the deep white layer VII of the SC adjacent to the periaqueductal gray. While R1 maps failed to reveal finer details, possibly due to the relatively coarse spatial sampling used for this modality, these could be recovered in R2* maps and in QSM. In the central part of the SC along its rostro-caudal axis, increased R2* values and decreased susceptibility values were observed 2 mm below the SC surface, likely reflecting the myelinated fibers in the superficial optic layer (layer III). Towards the deeper layers, a second increase in R2* was paralleled by a paramagnetic shift in QSM suggesting the presence of an iron-rich layer about 3 mm below the surface of the SC, attributed to the intermediate gray layer (IV) composed of multipolar neurons. These results dovetail observations in histological specimens and animal studies and demonstrate that high-resolution multi-modal MRI at 9.4T can reveal several microstructural features of the SC in vivo.

Spatial analysis and high resolution mapping of the human whole-brain transcriptome for integrative analysis in neuroimaging

The quantification of big pools of diverse molecules provides important insights on brain function, but is often restricted to a limited number of observations, which impairs integration with other modalities. To resolve this issue, a method allowing for the prediction of mRNA expression in the entire brain based on microarray data provided in the Allen Human Brain Atlas was developed. Microarray data of 3702 samples from 6 brain donors was registered to MNI and cortical surface space using FreeSurfer. For each of 18,686 genes, spatial dependence of transcription was assessed using variogram modelling. Variogram models were employed in Gaussian process regression to calculate best linear unbiased predictions for gene expression at all locations represented in well-established imaging atlases for cortex, subcortical structures and cerebellum. For validation, predicted whole-brain transcription of the HTR1A gene was correlated with [carbonyl-11C]WAY-100635 positron emission tomography data collected from 30 healthy subjects. Prediction results showed minimal bias ranging within ±0.016 (cortical surface), ±0.12 (subcortical regions) and ±0.14 (cerebellum) in units of log2 expression intensity for all genes. Across genes, the correlation of predicted and observed mRNA expression in leave-one-out cross-validation correlated with the strength of spatial dependence (cortical surface: r = 0.91, subcortical regions: r = 0.85, cerebellum: r = 0.84). 816 out of 18,686 genes exhibited a high spatial dependence accounting for more than 50% of variance in the difference of gene expression on the cortical surface. In subcortical regions and cerebellum, different sets of genes were implicated by high spatially structured variability. For the serotonin 1A receptor, correlation between PET binding potentials and predicted comprehensive mRNA expression was markedly higher (Spearman ρ = 0.72 for cortical surface, ρ = 0.84 for subcortical regions) than correlation of PET and discrete samples only (ρ = 0.55 and ρ = 0.63, respectively). Prediction of mRNA expression in the entire human brain allows for intuitive visualization of gene transcription and seamless integration in multimodal analysis without bias arising from non-uniform distribution of available samples. Extension of this methodology promises to facilitate translation of omics research and enable investigation of human brain function at a systems level.

T143. NOT A NUISANCE ANY MORE: GLOBAL FMRI SIGNAL AT REST, PROCESSING SPEED AND SYMPTOM SEVERITY IN SCHIZOPHRENIA

BackgroundBefore data from resting-state functional magnetic resonance imaging (rs-fMRI) is analyzed, the global signal (GS) - average blood-oxygen level dependent (BOLD) signal across all voxels in the brain - is normally removed through global signal regression (GSR). This convention arose in order to control for changes in brain activity that are usually of no interest but may be caused by non-neuronal factors, including changes in respiratory rate, arterial CO2 levels or cardiac pulsation. However, recent studies have indicated that GS may systematically vary between patients with schizophrenia and healthy controls. In addition to testing this notion, we also studied if the dynamic variance of global signal across time carried any meaningful information that relates to overall symptom severity and information processing speed in patients with schizophrenia.MethodsData was collected from 39 in a clinically stable, medicated early stage of schizophrenia (median duration of illness= 6.5 years), and 34 sex, age and parental socioeconomic-status matched healthy controls over a 10-minute period of eyes-open rest at TR=2.5s (3T Philips Achieva, 240 time points, dual-echo, gradient-echo EPI). Scores were obtained from the Signs and Symptoms of Psychotic Illness (SSPI) scale and the Digit Symbol Substitution Test (DSST). Rs-fMRI time-series data were motion-corrected (using 6 parameters), slice-time corrected, reoriented with structural images, band-pass filtered (0.01–0.1 Hz), scrubbed using ArtRepair for framewise displacement and transformed to MNI space. SPM8 and the advanced version of the Data Processing Assistant for resting-state fMRI (DPARSFA) were used for this purpose. GS mean was computed from all grey matter voxels using a template mask in MNI space, using grand mean scaling to a base of 1000, averaged across all time-points. The variance of GS across time (dynamic GS variance) was computed from the entire 10-minutes of acquisition (240 time points).ResultsIndependent-sample t-tests used to compare GS mean between controls (mean[sd] = 3135.1[1244.4]) and the SCZ group (mean[sd] = 3207.8[1191.7]) yielded no significant results [t(71) = -0.14, p = .89]. The temporal variance of GS did not differ between controls (mean[sd] = 113.05[59.41]) and the SCZ group (mean[sd] = 118.02[57.93]) [t(71) = -0.36, p = .72]. In the SCZ group there was a significant correlation between the total SSPI score reflecting overall illness severity (□ = -.322, p < 0.05) and the mean GS. This relationship was especially pronounced for the syndrome of Reality Distortion (rho = -.344, p < 0.05) and Disorganization (rho = -.303, p = 0.065), where higher symptom severity was seen in patients with lower mean GS.Dynamic variance in GS was higher in healthy controls with lower mean DSST (r = -.364, p = 0.04), but no such relationship was seen in the SCZ group (r = .066, p = .694). Notably, when compared to controls (mean[sd] = 57.4[9.40]), patients (mean[sd]=42.4[9.97]) had significantly lower DSST scores [t(69) = 6.47, p < 0.001]. Neither GS nor GS variance related to root mean square of framewise displacement in the 2 groups.DiscussionWe did not find an overall increase or reduction in the global signal in patients with schizophrenia. Nevertheless, the strength of global signal obtained from resting fMRI is related to severity of persisting symptoms of schizophrenia, whereas the dynamic variance of this signal relates to the speed of processing ability assessed outside the scanner in healthy subjects. With emerging evidence relating global signal to cognitive vigilance and overall brain connectivity, our results indicate that global signal is a parameter of interest that should not be automatically discarded in resting fMRI studies of schizophrenia

F162. MORE EFFORT, BUT LESS EFFICIENCY - WORKING MEMORY IN SCHIZOPHRENIA: AN INVESTIGATION INTO CAUSE FOR DIVERGENT RESULTS

BackgroundFunctional brain imaging studies of working memory in people with schizophrenia have reported divergent reports with some studies reporting hypofrontal activation while report hypofrontal activation. The inconsistencies in the literature have been postulated to be related to task requirements or poor task performance in schizophrenia. An alternative hypothesis proposed is that different regions within the PFC show either hypo or hyperactivity, depending on their location. In view of the inconsistencies in previous research, the aim of the current research is to examine abnormalities in a cohort of partially remitted people with schizophrenia and matched controlsMethodsTwenty people with schizophrenia and 20 matched healthy controls (matched on age, gender and parental social and economic status) were selected from the Nottingham area to undergo a functional magnetic resonance imaging (fMRI) scan while undergoing two levels of the visual n-back task (zeroback and two back). The behavioural results (latency and accuracy) on the nback task was compared using repeated measures analysis. The MR images were reoriented, realigned, co-registered to the T1-weighted anatomical image, and normalised to the MNI space. Normalised images were resliced to a voxel size of 3 mm3, smoothed with an 8 mm full-width half-maximum Gaussian kernel using SPM 5. The GLM approach implemented in SPM 5 was utilized for fMRI data modeling and analyses. Each epoch type (zero-back, two-back and rest) was modeled in a boxcar design, using a canonical hemodynamic response function and its temporal derivative. The single group second level analysis consisted of voxelwise one-sample t-tests with significance threshold set at voxel level p < .05, false discovery rate (FDR) corrected for multiple comparisons across the entire brain.The between-group comparison employed voxelwise two sample t-tests with the significance criterion based on the spatial extent of suprathreshold voxel clusters, a method proposed by (Friston et al., 1994). The criterion for inclusion of a voxel in a cluster was set at p < .05 (uncorrected) and a cluster was considered as significant at level of p < .05 (corrected).ResultsPatients exhibited relatively high general function and mild symptoms, but had significantly longer reaction time and decline in performance. Both controls and patients activated similar set of brain regions similar to Central executive network and deactivated brain areas comprising the default mode network. Most noteworthy, we did not find evidence for hypofrontality (reduced activity in DLPFC in patients compared to controls) in this study. Compared to controls, patients showed areas of greater activation in left postcentral gyrus, anterior and posterior medial frontal gyrus and left superior temporal gyrus.DiscussionBoth controls and patients showed activation in widespread brain areas consistent with the CEN, and deactivation in areas consistent with DMN regions. There was no evidence of hypofrontality in this sample of remitted people with schizophrenia. Patients showed activation patterns on the zeroback task similar to the activation patterns for controls on the two back task, suggesting that patients showed increased brain activation on a task with lesser requirements, though behavioural results suggest inefficiency despite the increased effort.

Diagnostic and prognostic value of amyloid PET textural and shape features: comparison with classical semi-quantitative rating in 760 patients from the ADNI-2 database.

We evaluated the performance of amyloid PET textural and shape features in discriminating normal and Alzheimer's disease (AD) subjects, and in predicting conversion to AD in subjects with mild cognitive impairment (MCI) or significant memory concern (SMC). Subjects from the Alzheimer's Disease Neuroimaging Initiative with available baseline 18F-florbetapir and T1-MRI scans were included. The cross-sectional cohort consisted of 181 controls and 148AD subjects. The longitudinal cohort consisted of 431 SMC/MCI subjects, 85 of whom converted to AD during follow-up. PET images were normalized to MNI space and post-processed using in-house software. Relative retention indices (SUVr) were computed with respect to pontine, cerebellar, and composite reference regions. Several textural and shape features were extracted then combined using a support vector machine (SVM) to build a predictive model of AD conversion. Diagnostic and prognostic performance was evaluated using ROC analysis and survival analysis with the Cox proportional hazard model. The three SUVr and all the tested features effectively discriminated AD subjects in cross-sectional analysis (all p < 0.001). In longitudinal analysis, the variables with the highest prognostic value were composite SUVr (AUC 0.86; accuracy 81%), skewness (0.87; 83%), local minima (0.85; 79%), Geary's index (0.86; 81%), gradient norm maximal argument (0.83; 82%), and the SVM model (0.91; 86%). The adjusted hazard ratio for AD conversion was 5.5 for the SVM model, compared with 4.0, 2.6, and 3.8 for cerebellar, pontine and composite SUVr (all p < 0.001), indicating that appropriate amyloid textural and shape features predict conversion to AD with at least as good accuracy as classical SUVr.

Functional architecture of the somatosensory homunculus detected by electrostimulation.

We performed a prospective electrostimulation study, based on 50 operated intact patients, to acquire accurate MNI coordinates of the functional areas of the somatosensory homunculus. In the contralateral BA1, the hand representation displayed not only medial-to-lateral, little-finger-to-thumb, but also rostral-to-caudal discrete somatotopy, with the tip of each finger located more caudally than the proximal phalanx. The analysis of the MNI body coordinates showed rare inter-individual variations in the medial-to-lateral somatotopic organization in these patients with rather different intensity thresholds needed to elicit sensations in different body parts. We found some similarities but also substantial differences with the previous, seminal works of Penfield and his colleagues. We propose a new drawing of the human somatosensory homunculus according to MNI space. In this prospective electrostimulation study, based on 50 operated patients with no sensory deficit and no brain lesion in the postcentral gyrus, we acquired coordinates in the standard MNI space of the functional areas of the somatosensory homunculus. The 3D brain volume of each patient was normalized to that space to obtain the MNI coordinates of the stimulation site locations. For 647 sites stimulated on Brodmann Area 1 (and 1025 in gyri nearby), 258 positive points for somatosensory response (40%) were found in the postcentral gyrus. In the contralateral BA1, the hand representation displayed not only medial-to-lateral and little-finger-to-thumb somatotopy, but also rostral-to-caudal discrete somatotopy, with the tip of each finger located more caudally than the proximal phalanx. We detected a medial-to-lateral, tip-to-base tongue organization but no rostral-to-caudal functional organization. The analysis of the MNI body coordinates showed rare inter-individual variations in the medial-to-lateral somatotopic organization in these patients with intact somatosensory cortex. Positive stimulations were detected through the 'on/off' outbreak effect and discriminative touch sensations were the sensations reported almost exclusively by all patients during stimulation. Mean hand (2.39mA) and tongue (2.60mA) positive intensity thresholds were lower (P<0.05) than the intensities required to elicit sensations in the other parts of the body. Unlike the previous, seminal works of Penfield and colleagues, we detected no sensations such as sense of movement or desire to move, no somatosensory responses outside the postcentral gyrus, and no bilateral responses for face/tongue stimulations. We propose a rationalization of the standard drawing of the somatosensory homunculus according to MNI space.

7T MRI subthalamic nucleus atlas for use with 3T MRI

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) reduces motor symptoms in most patients with Parkinson disease (PD), yet may produce untoward effects. Investigation of DBS effects requires accurate localization of the STN, which can be difficult to identify on magnetic resonance images collected with clinically available 3T scanners. The goal of this study is to develop a high-quality STN atlas that can be applied to standard 3T images. We created a high-definition STN atlas derived from seven older participants imaged at 7T. This atlas was nonlinearly registered to a standard template representing 56 patients with PD imaged at 3T. This process required development of methodology for nonlinear multimodal image registration. We demonstrate mm-scale STN localization accuracy by comparison of our 3T atlas with a publicly available 7T atlas. We also demonstrate less agreement with an earlier histological atlas. STN localization error in the 56 patients imaged at 3T was less than 1mm on average. Our methodology enables accurate STN localization in individuals imaged at 3T. The STN atlas and underlying 3T average template in MNI space are freely available to the research community. The image registration methodology developed in the course of this work may be generally applicable to other datasets.

Accuracy of different three-dimensional subcortical human brain atlases for DBS -lead localisation.

BackgroundAccurate interindividual comparability of deep brain stimulation (DBS) lead locations in relation to the surrounding anatomical structures is of eminent importance to define and understand effective stimulation areas. The objective of the current work is to compare the accuracy of the DBS lead localisation relative to the STN in native space with four recently developed three-dimensional subcortical brain atlases in the MNI template space. Accuracy is reviewed by anatomical and volumetric analysis as well as intraoperative electrophysiological data.MethodsPostoperative lead localisations of 10 patients (19 hemispheres) were analysed in each individual patient based on Brainlab software (native space) and after normalization into the MNI space and application of 4 different human brain atlases using Lead-DBS toolbox within Matlab (template space). Each patient's STN was manually segmented and the relation between the reconstructed lead and the STN was compared to the 4 atlas-based STN models by applying the Dice coefficient. The length of intraoperative electrophysiological STN activity along different microelectrode recording tracks was measured and compared to reconstructions in native and template space. Descriptive non-parametric statistical tests were used to calculate differences between the 4 different atlases.ResultsThe mean STN volume of the study cohort was 153.3 ± 40.3 mm3 (n = 19). This is similar to the STN volume of the DISTAL atlas (166 mm3; p = .22), but significantly larger compared to the other atlases tested in this study. The anatomical overlap of the lead-STN-reconstruction was highest for the DISTAL atlas (0.56 ± 0.18) and lowest for the PD25 atlas (0.34 ± 0.17). A total number of 47 MER trajectories through the STN were analysed. There was a statistically significant discrepancy of the electrophysiogical STN activity compared to the reconstructed STN of all four atlases (p < .0001).Conclusion: Lead reconstruction after normalization into the MNI template space and application of four different atlases led to different results in terms of the DBS lead position relative to the STN. Based on electrophysiological and imaging data, the DISTAL atlas led to the most accurate display of the reconstructed DBS lead relative to the DISTAL-based STN.

A probabilistic atlas of human brainstem pathways based on connectome imaging data

The brainstem is a critical structure that regulates vital autonomic functions, houses the cranial nerves and their nuclei, relays motor and sensory information between the brain and spinal cord, and modulates cognition, mood, and emotions. As a primary relay center, the fiber pathways of the brainstem include efferent and afferent connections among the cerebral cortex, spinal cord, and cerebellum. While diffusion MRI has been successfully applied to map various brain pathways, its application for the in vivo imaging of the brainstem pathways has been limited due to inadequate resolution and large susceptibility-induced distortion artifacts. With the release of high-resolution data from the Human Connectome Project (HCP), there is increasing interest in mapping human brainstem pathways. Previous works relying on HCP data to study brainstem pathways, however, did not consider the prevalence (>80%) of large distortions in the brainstem even after the application of correction procedures from the HCP-Pipeline. They were also limited in the lack of adequate consideration of subject variability in either fiber pathways or region of interests (ROIs) used for bundle reconstruction. To overcome these limitations, we develop in this work a probabilistic atlas of 23 major brainstem bundles using high-quality HCP data passing rigorous quality control. For the large-scale data from the 500-Subject release of HCP, we conducted extensive quality controls to exclude subjects with severe distortions in the brainstem area. After that, we developed a systematic protocol to manually delineate 1300 ROIs on 20 HCP subjects (10 males; 10 females) for the reconstruction of fiber bundles using tractography techniques. Finally, we leveraged our novel connectome modeling techniques including high order fiber orientation distribution (FOD) reconstruction from multi-shell diffusion imaging and topography-preserving tract filtering algorithms to successfully reconstruct the 23 fiber bundles for each subject, which were then used to calculate the probabilistic atlases in the MNI152 space for public release. In our experimental results, we demonstrate that our method yielded anatomically faithful reconstruction of the brainstem pathways and achieved improved performance in comparison with an existing atlas of cerebellar peduncles based on HCP data. These atlases have been publicly released on NITRIC (https://www.nitrc.org/projects/brainstem_atlas/) and can be readily used by brain imaging researchers interested in studying brainstem pathways.

White Matter Changes Correlates of Peripheral Neuroinflammation in Patients with Parkinson’s Disease

Neuroinflammatory pathology has long been identified to contribute to the pathology of Parkinson disease. Early microstructural changes in white matter tracts might give a clue for earlier detection of PD. We investigated through diffusion MRI connectometry the structural correlates of white matter tracts of 81 patients with PD with whole blood neutrophil-to-lymphocyte ratio (NLR), controlling for age and sex. Diffusion data were reconstructed in the MNI space using q-space diffeomorphic reconstruction to obtain the spin distribution function. The spin distribution function (SDF) values were used in DMRI connectometry analysis. The connectometry analyses identified white matter QA of the following fibers to be correlated with NLR score after adjustment for age and sex: bilateral cingulum, body and left crus of fornix, bilateral corticospinal tract (CST), and body and splenium of corpus callosum (CC) and superior cerebellar peduncle with decreased connectivity related to NLR (FDR = 0.04542). Keeping with emerging evidence on the role of neuroinflammation in PD pathology, these results with functional relevance to prodromal Parkinson disease, bring new insights to pivotal role of peripheral inflammation in CNS neurodegeneration.

High thickness histological sections as alternative to study the three-dimensional microscopic human sub-cortical neuroanatomy.

Stereotaxy is based on the precise image-guided spatial localization of targets within the human brain. Even with the recent advances in MRI technology, histological examination renders different (and complementary) information of the nervous tissue. Although several maps have been selected as a basis for correlating imaging results with the anatomical locations of sub-cortical structures, technical limitations interfere in a point-to-point correlation between imaging and anatomy due to the lack of precise correction for post-mortem tissue deformations caused by tissue fixation and processing. We present an alternative method to parcellate human brain cytoarchitectural regions, minimizing deformations caused by post-mortem and tissue-processing artifacts and enhancing segmentation by means of modified high thickness histological techniques and registration with MRI of the same specimen and into MNI space (ICBM152). A three-dimensional (3D) histological atlas of the human thalamus, basal ganglia, and basal forebrain cholinergic system is displayed. Structure's segmentations were performed in high-resolution dark-field and light-field microscopy. Bidimensional non-linear registration of the histological slices was followed by 3D registration with in situ MRI of the same subject. Manual and automated registration procedures were adopted and compared. To evaluate the quality of the registration procedures, Dice similarity coefficient and normalized weighted spectral distance were calculated and the results indicate good overlap between registered volumes and a small shape difference between them in both manual and automated registration methods. High thickness high-resolution histological slices in combination with registration to in situ MRI of the same subject provide an effective alternative method to study nuclear boundaries in the human brain, enhancing segmentation and demanding less resources and time for tissue processing than traditional methods.

Reliable and Reproducible GABA Measurements Using Automated Spectral Prescription at Ultra-High Field

Purpose: To evaluate spectral acquisition processes important for obtaining reliable and reproducible γ-aminobutyric acid (GABA) signals from volunteers in brain regions that are frequently used for neuroimaging studies [anterior cingulate cortex (ACC), superior temporal gyrus, and caudate] at ultra-high field.Methods: Ten healthy volunteers were studied using a single-voxel Point-RESolved Spectrosocpy (PRESS) sequence with band selective inversion with gradient dephasing pulses (BASING). The editing pulse was designed to be symmetrically placed at 2.0 and 1.4 ppm in the two cycles to reduce the co-editing of macro-molecules (MM). Spectral data were obtained with phase encoding matrix 8 × 8 × 1 and two editing cycles or 1 × 1 × 1 and 64 editing/64 non-editing. The total acquisition time was approximately 4.5 min for each acquisition. An automated MRS prescription method was utilized for the placement of the GABA scan location in 5/10 subjects. Three regions of interest were predefined in the MNI152 space and then registered and transformed to subject space. These volunteers also had repeat scans to examine between-session reproducibility.Results: The placement of editing pulses symmetrically at 1.7 ppm reduced the effect of MM contributions and provided more accurate GABA estimation. Chemical shift misregistration errors caused by classic PRESS localization sequence are more significant at ultra-high field strength. Therefore, a large over-excitation factor was needed to reduce this error. Furthermore, the inefficiency of saturation bands and unspoiled coherence could also interfere with the quality of the data. Reliable recovery of metabolite signals resulted from the implementation of 8 × 8 × 1 phase encoding that successfully removed artifacts and errors, without compromising the total acquisition time. Between successive scans on the same subject, dice overlap ratios of the excited spectral volume between the two scans were in the range of 92–95%. Within subject variability of metabolites between two repeat scans was smaller in the ACC and left superior temporal gyrus when compared to that in the right caudate, with averaged coefficients of variation being 3.6, 6.0, and 16.9%, respectively.Conclusion: This study demonstrated the feasibility of obtaining reliable and reproducible GABA measurements at ultra-high field.