Dual Regression Method Research Articles

Longitudinal default mode sub-networks in the language and visual variants of Alzheimer's disease.

Disruption of the default mode network is a hallmark of Alzheimer's disease, which has not been extensively examined in atypical phenotypes. We investigated cross-sectional and 1-year longitudinal changes in default mode network sub-systems in the visual and language variants of Alzheimer's disease, in relation to age and tau. Sixty-one amyloid-positive Alzheimer's disease participants diagnosed with posterior cortical atrophy (n = 33) or logopenic progressive aphasia (n = 28) underwent structural MRI, resting-state functional MRI and [18F]flortaucipir PET. One-hundred and twenty-two amyloid-negative cognitively unimpaired individuals and 60 amyloid-positive individuals diagnosed with amnestic Alzheimer's disease were included as controls and as a comparison group, respectively, and had structural and resting-state functional MRI. Forty-one atypical Alzheimer's disease participants, 26 amnestic Alzheimer's disease participants and 40 cognitively unimpaired individuals had one follow-up functional MRI ∼1-2 years after the baseline scan. Default mode network connectivity was calculated using the dual regression method for posterior, ventral, anterior ventral and anterior dorsal sub-systems derived from independent component analysis. A global measure of default mode network connectivity, the network failure quotient, was also calculated. Linear mixed-effects models and voxel-based analyses were computed for each connectivity measure. Both atypical and amnestic Alzheimer's disease participants had lower cross-sectional posterior and ventral and higher anterior dorsal connectivity and network failure quotient relative to cognitively unimpaired individuals. Age had opposite effects on connectivity in Alzheimer's disease participants and cognitively unimpaired individuals. While connectivity declined with age in cognitively unimpaired individuals, younger Alzheimer's disease participants had lower connectivity than the older ones, particularly in the ventral default mode network. Greater baseline tau-PET uptake was associated with lower ventral and anterior ventral default mode network connectivity in atypical Alzheimer's disease. Connectivity in the ventral default mode network declined over time in atypical Alzheimer's disease, particularly in older participants, with lower tau burden. Voxel-based analyses validated the findings of higher anterior dorsal default mode network connectivity, lower posterior and ventral default mode network connectivity and decline in ventral default mode network connectivity over time in atypical Alzheimer's disease. Visuospatial symptoms were associated with default mode network connectivity disruption. In summary, default mode connectivity disruption was similar between atypical and amnestic Alzheimer's disease variants, and discriminated Alzheimer's disease from cognitively unimpaired individuals, with decreased posterior and increased anterior connectivity and with disruption more pronounced in younger participants. The ventral default mode network declined over time in atypical Alzheimer's disease, suggesting a shift in default mode network connectivity likely related to tau pathology.

Default mode network sub‐systems connectivity in atypical Alzheimer’s disease

AbstractBackgroundDisruption of default mode network (DMN) connectivity is common in Alzheimer’s disease. We investigated cross‐sectional and one‐year longitudinal changes in DMN sub‐systems in atypical clinical presentations of AD, in relation to age and tau.MethodSixty‐four amyloid‐positive atypical AD (Aty‐AD) patients diagnosed with posterior cortical atrophy (n = 35) or logopenic progressive aphasia (n = 29) were recruited by the Neurodegenerative Research Group. Patients underwent structural and resting‐state functional MRI, and [18F]flortaucipir PET at baseline and one‐year follow‐up. 140 amyloid‐negative cognitively unimpaired (CU) individuals from the Mayo Clinic Study of Aging were included as controls. Global tau SUVR was calculated in a meta‐ROI including parietal, temporal, and occipital regions. DMN connectivity was calculated in native space for posterior (pDMN), ventral (vDMN), anterior ventral (avDMN) and anterior dorsal (adDMN) DMN sub‐systems using the dual regression method. A global measure of DMN connectivity, the Network Failure Quotient (NFQ), was calculated as (vDMN_to_pDMN+ adDMN_to_pDMN)/(pDMN+vDMN). Linear mixed‐effects models were computed for each DMN connectivity measure, including diagnosis (Aty‐AD, CU), age, time and their interaction, and a per‐person random effect. SPM paired t‐tests were run to compare baseline and follow‐up images in Aty‐AD and CU separately. Linear mixed‐effect models were run in the Aty‐AD cohort only to investigate the effect of global baseline tau SUVR on each DMN connectivity measure.ResultMixed‐effects models showed evidence of lower cross‐sectional pDMN and higher adDMN connectivity in Aty‐AD relative to CU, with no significant time effects (Fig. 1). While connectivity in all DMN sub‐systems declined with age in CU, connectivity was higher in older Aty‐AD patients relative to younger, particularly in vDMN and pDMN. A similar trend was observed for NFQ, which was significantly higher in Aty‐AD, with a negative age effect (Fig. 1). In Aty‐AD, voxel‐based analyses showed moderate evidence of decline in vDMN connectivity and increase in avDMN connectivity over time (Fig. 2). Greater baseline global tau SUVR was associated with lower vDMN connectivity, cross‐sectionally and longitudinally (Fig. 3).ConclusionDMN connectivity was altered in Aty‐AD, with strongest alterations in younger patients. The vDMN declined over time, suggesting a shift in DMN connectivity with disease progression that was likely related to tau pathology.

Default mode network sub‐systems connectivity in atypical Alzheimer’s disease

AbstractBackgroundDisruption of default mode network (DMN) connectivity is common in Alzheimer’s disease. We investigated cross‐sectional and one‐year longitudinal changes in DMN sub‐systems in atypical clinical presentations of AD, in relation to age and tau.MethodSixty‐four amyloid‐positive atypical AD (Aty‐AD) patients diagnosed with posterior cortical atrophy (n = 35) or logopenic progressive aphasia (n = 29) were recruited by the Neurodegenerative Research Group. Patients underwent structural and resting‐state functional MRI, and [18F]flortaucipir PET at baseline and one‐year follow‐up. 140 amyloid‐negative cognitively unimpaired (CU) individuals from the Mayo Clinic Study of Aging were included as controls. Global tau SUVR was calculated in a meta‐ROI including parietal, temporal, and occipital regions. DMN connectivity was calculated in native space for posterior (pDMN), ventral (vDMN), anterior ventral (avDMN) and anterior dorsal (adDMN) DMN sub‐systems using the dual regression method. A global measure of DMN connectivity, the Network Failure Quotient (NFQ), was calculated as (vDMN_to_pDMN+ adDMN_to_pDMN)/(pDMN+vDMN). Linear mixed‐effects models were computed for each DMN connectivity measure, including diagnosis (Aty‐AD, CU), age, time and their interaction, and a per‐person random effect. SPM paired t‐tests were run to compare baseline and follow‐up images in Aty‐AD and CU separately. Linear mixed‐effect models were run in the Aty‐AD cohort only to investigate the effect of global baseline tau SUVR on each DMN connectivity measure.ResultMixed‐effects models showed evidence of lower cross‐sectional pDMN and higher adDMN connectivity in Aty‐AD relative to CU, with no significant time effects (Fig. 1). While connectivity in all DMN sub‐systems declined with age in CU, connectivity was higher in older Aty‐AD patients relative to younger, particularly in vDMN and pDMN. A similar trend was observed for NFQ, which was significantly higher in Aty‐AD, with a negative age effect (Fig. 1). In Aty‐AD, voxel‐based analyses showed moderate evidence of decline in vDMN connectivity and increase in avDMN connectivity over time (Fig. 2). Greater baseline global tau SUVR was associated with lower vDMN connectivity, cross‐sectionally and longitudinally (Fig. 3).ConclusionDMN connectivity was altered in Aty‐AD, with strongest alterations in younger patients. The vDMN declined over time, suggesting a shift in DMN connectivity with disease progression that was likely related to tau pathology.

Alterations in Resting-State Functional Brain Connectivity and Correlations with Vestibular/Ocular-Motor Screening Measures in Postconcussion Vestibular Dysfunction.

Vestibular symptoms after concussion are common and associated with protracted recovery. The purpose of this study is to define resting-state functional MRI (rs-fMRI) brain connectivity alterations in patients with postconcussion vestibular dysfunction (PCVD) and correlations between rs-fMRI connectivity and symptoms provoked during Vestibular/Ocular-Motor Screening (VOMS) assessment. Prospective IRB approved study. 12 subjects with subacute PCVD (2-10 weeks); control group: 10 age-matched subjects without history of concussion or vestibular impairment. Both groups underwent clinical vestibular assessment. rs-fMRI was acquired on 3.0T Siemens Trio with a 12-channel head coil. rs-fMRI data analysis included independent component analysis-based functional connectivity group differences, graph theory analysis, and ROI-to-ROI connectivity correlation analysis with VOMS clinical derivatives. Group difference maps between resting-state networks were calculated using dual regression method and corrected for multiple comparisons. Correlation analysis between ROI-to-ROI rs-fMRI brain activation and VOMS assessment ratings was performed using Pearson correlation coefficient, with a significance threshold of P ≤ .05. Compared to controls, PCVD group demonstrated significantly increased rs-fMRI connectivity between the default-mode network and right middle frontal gyrus and right postcentral gyrus; and between a vestibular-sensorimotor network and right prefrontal cortex. Significant positive correlations were found between clinical derivative VOMS scores and components of the vestibular, visual networks, and multisensory processing cortical representations. Altered rs-fMRI brain connectivity with increased connectivity of visual input, multisensory processing, and spatial memory in PCVD is correlative with clinical derivative VOMS scores, suggesting maladaptive brain plasticity underlying vestibular symptomatology.

Eigenvector Centrality Dynamics From Resting-State fMRI: Gender and Age Differences in Healthy Subjects.

With the increasing use of functional brain network properties as markers of brain disorders, efficient visualization and evaluation methods have become essential. Eigenvector centrality mapping (ECM) of functional MRI (fMRI) data enables the representation of per-node graph theoretical measures as brain maps. This paper studies the use of centrality dynamics for measuring group differences in imaging studies. Imaging data were used from a publicly available imaging study, which included resting fMRI data. After warping the images to a standard space and masking cortical regions, ECM were computed in a sliding window. The dual regression method was used to identify dynamic centrality differences inside well-known resting-state networks between gender and age groups. Gender-related differences were found in the medial and lateral visual, motor, default mode, and executive control RSN, where male subjects had more consistent centrality variations within the network. Age-related differences between the youngest and oldest subjects, based on a median split, were found in the medial visual, executive control and left frontoparietal networks, where younger subjects had more consistent centrality variations within the network. Our findings show that centrality dynamics can be used to identify between-group functional brain network centrality differences, and that age and gender distributions studies need to be taken into account in functional imaging studies.

Cholinergic and serotonergic modulation of resting state functional brain connectivity in Alzheimer's disease

Disruption of cholinergic and serotonergic neurotransmitter systems is associated with cognitive, emotional and behavioural symptoms of Alzheimer's disease (AD). To investigate the responsiveness of these systems in AD we measured the effects of a single-dose of the selective serotonin reuptake inhibitor citalopram and acetylcholinesterase inhibitor galantamine in 12 patients with AD and 12 age-matched controls on functional brain connectivity with resting state functional magnetic resonance imaging. In this randomized, double blind, placebo-controlled crossover study, functional magnetic resonance images were repeatedly obtained before and after dosing, resulting in a dataset of 432 scans. Connectivity maps of ten functional networks were extracted using a dual regression method and drug vs. placebo effects were compared between groups with a multivariate analysis with signals coming from cerebrospinal fluid and white matter as covariates at the subject level, and baseline and heart rate measurements as confound regressors in the higher-level analysis (at p < 0.05, corrected). A galantamine induced difference between groups was observed for the cerebellar network. Connectivity within the cerebellar network and between this network and the thalamus decreased after galantamine vs. placebo in AD patients, but not in controls. For citalopram, voxelwise network connectivity did not show significant group × treatment interaction effects. However, we found default mode network connectivity with the precuneus and posterior cingulate cortex to be increased in AD patients, which could not be detected within the control group. Further, in contrast to the AD patients, control subjects showed a consistent reduction in mean connectivity with all networks after administration of citalopram. Since AD has previously been characterized by reduced connectivity between the default mode network and the precuneus and posterior cingulate cortex, the effects of citalopram on the default mode network suggest a restoring potential of selective serotonin reuptake inhibitors in AD. The results of this study also confirm a change in cerebellar connections in AD, which is possibly related to cholinergic decline.

Effects of mild traumatic brain injury and post-traumatic stress disorder on resting-state default mode network connectivity

Mild traumatic brain injury (mTBI) and post-traumatic stress disorder (PTSD) are common outcomes for service members. Abnormal connectivity within neural networks has been reported in the resting brain of mTBI and PTSD patients, respectively; however, the potential role of PTSD in changes to neural networks following injury has not been studied in detail. Using a data-driven approach, the present analysis aimed to elucidate resting state functional connectivity in the default mode network (DMN) in those with mTBI only and those with comorbid mTBI and PTSD. A secondary analysis focused on distinct contributions by the anterior and posterior DMN components. Group-level independent component analysis was used to identify the DMN, and a dual-regression method was utilized to measure connectivity within the overall network and its anterior (medial prefrontal cortex) and posterior (posterior cingulate cortex) nodes. Connectivity within the overall DMN was significantly higher for the mTBI only group (p = 0.001), as compared to controls and mTBI + PTSD. For all subjects with mTBI, network connectivity correlated inversely with PTSD checklist score (p < 0.05). Additionally, distinct associations (p < 0.05) between medial prefrontal cortex connectivity and PTSD symptoms and, separately, posterior cingulate cortex connectivity and mTBI-related cognitive deficits were found. To our knowledge, this is the first study to report a differential relationship between DMN components and both post-traumatic symptoms and cognitive outcomes.

INTRINSIC BRAIN NETWORKS OF COGNITIVE COMPONENTS IN SUBJECTIVE COGNITIVE DECLINE

Subjective cognitive decline (SCD) is described with unimpaired performance on standardized neuropsychological tests and is increasingly considered as a valuable stage of carrying out early intervention studies on Alzheimer's disease (AD). Demonstrated by MRI, individuals with SCD exhibited abnormal patterns of brain activation with various cognitive tasks and functional connectivity with resting state networks. A link between the brain activity during task performance and their connectivity has been missing in SCD. We target a comprehensive delineation of this link in SCD by elucidating intrinsic connectivity networks (ICNs) of cognitive components from previous studies with task fMRI (tfMRI). Forty-two individuals with SCD and 42 healthy elders, matched by age, sex and level of education, participated in this study. Their ICNs are reconstructed with the reliable dual-regression method from individual resting-state fMRI (rfMRI) images. A machine-learning algorithm to 10,449 tfMRI papers generated 12 template maps of the dual-regression. General linear models are employed to examine group differences in the 12 ICNs and their interactions with sex. All the cognitive components are illustrated by their ICN profiles as in Figure 1, indicating what brain areas are highly-connected regarding their rfMRI data while they are commonly activated by tasks recruiting the same cognitive component. While auditory component showed enhanced connectivity strength with the default network in its posterior cingulate cortex node in females, surprisingly no any diagnosis-related changes are detected (Figure 2). Further investigation of the diagnosis-sex interactions found that the basal component demonstrated such effect on its connectivity with the right supramarginal gyrus (sensory motor network). Scatter plots of this interaction (Figure 3) revealed that the connectivity is enhanced (more negative) in males with SCD whereas it is weakened (more positive) females with SCD.

Resting-State Functional Connectivity in Patients with Long-Term Remission of Cushing's Disease.

Glucocorticoid disturbance can be a cause of psychiatric symptoms. Cushing's disease represents a unique model for examining the effects of prolonged exposure to high levels of endogenous cortisol on the human brain as well as for examining the relation between these effects and psychiatric symptomatology. This study aimed to investigate resting-state functional connectivity (RSFC) of the limbic network, the default mode network (DMN), and the executive control network in patients with long-term remission of Cushing's disease. RSFC of these three networks of interest was compared between patients in remission of Cushing's disease (n=24; 4 male, mean age=44.96 years) and matched healthy controls (n=24; 4 male, mean age=46.5 years), using probabilistic independent component analysis to extract the networks and a dual regression method to compare both groups. Psychological and cognitive functioning was assessed with validated questionnaires and interviews. In comparison with controls, patients with remission of Cushing's disease showed an increased RSFC between the limbic network and the subgenual subregion of the anterior cingulate cortex (ACC) as well as an increased RSFC of the DMN in the left lateral occipital cortex. However, these findings were not associated with psychiatric symptoms in the patient group. Our data indicate that previous exposure to hypercortisolism is related to persisting changes in brain function.

Longitudinal resting state fMRI analysis in healthy controls and premanifest Huntington's disease gene carriers: a three-year follow-up study.

We previously demonstrated that in the premanifest stage of Huntington's disease (preHD), a reduced functional connectivity exists compared to healthy controls. In the current study, we look at possible changes in functional connectivity occurring longitudinally over a period of 3 years, with the aim of assessing the potential usefulness of this technique as a biomarker for disease progression in preHD. Twenty-two preHD and 17 healthy control subjects completed resting state functional magnetic resonance imaging (fMRI) scans in two visits with 3 years in between. Differences in resting state connectivity were examined for eight networks of interest using FSL with three different analysis types: a dual regression method, region of interest approach, and an independent component analysis. To evaluate a possible combined effect of gray matter volume change and the change in blood oxygenation level dependent signal, the analysis was performed with and without voxel-wise correction for gray matter volume. To evaluate possible correlations between functional connectivity change and the predicted time to disease onset, the preHD group was classed as preHD-A if ≥10.9 years and preHD-B if <10.9 years from predicted disease onset. Possible correlations between burden of pathology score and functional connectivity change in preHD were also assessed. Finally, longitudinal change in whole brain and striatal volumetric measures was assessed in the studied cohort. Longitudinal analysis of the resting state-fMRI (RS-fMRI) data revealed no differences in the degree of connectivity change between the groups over a period of 3 years, though a significantly higher rate of striatal atrophy was found in the preHD group compared to controls in the same period. Based on the results found in this study, the provisional conclusion is that RS-fMRI lacks sensitivity in detecting changes in functional connectivity in HD gene carriers prior to disease manifestation over a 3-year follow-up period.

Resting state functional hyperconnectivity within a triple network model in paranoid schizophrenia

BackgroundThree large-scale intrinsic connectivity brain networks, the salience network (SN), the central executive network (CEN), and the default mode network (DMN), have fundamental roles in higher cognitive processes. In particular, SN activity is crucial in the process of salience mapping—ie, allocating attentional resources to external and internal stimuli and attributing salience to the stimuli. Recent functional neuroimaging studies suggest that the core psychopathological changes in schizophrenia could arise from aberrant connectivity (dysconnectivity) within large scale networks in the brain. However, studies have yielded inconsistent results and have largely been unsuccessful at mapping these abnormalities to core psychopathology. The triple network model of aberrant saliency mapping suggests that the dysconnectivity underlying the psychopathology could lie within these three core brain networks. We hypothesised that intrinsic connectivity within these brain networks is altered in schizophrenia when compared with healthy adults. MethodsWe assessed 37 medicated patients with paranoid schizophrenia (Diagnostic and Statistical Manual of Mental Disorders IV-295.3) and 37 age-matched and sex-matched controls from the Center for Biomedical Research Excellence dataset. We did a group-level independent component analysis on resting-state functional MRI to extract 30 group-level spatial intrinsic connectivity (IC) maps (FSL, FMRIB Software Library). From the group-level IC maps, we identified maps corresponding to the SN, DMN, and CEN. Then, we estimated a version of the group-level spatial map for each individual using the dual regression method and established between-group differences using permutation tests. Using a sparse logistic regression method, we also assessed whether IC maps could predict group membership (patient vs healthy controls) and, with a similar method, whether the IC maps could predict psychotic symptomatology (the positive and negative syndrome scale [PANSS]). FindingsThe schizophrenia group showed stronger functional connectivity within the left CEN, SN, and DMN than did controls. When we used leave-one-out cross-validation, the SN map best discriminated patients from controls with 82·4% accuracy, 94·6 % sensitivity, and 70% specificity. In addition, the SN maps predicted the severity of positive symptoms score on the PANSS (r2=0·95, p<0·0001), particularly delusions (r2=0·38, p=0·003). DMN hyperconnectivity predicted negative symptoms score (r2=0·98, p=0·0005). InterpretationThe SN, CEN, and DMN in paranoid schizophrenia are characterised by significant hyperconnectivity. SN hyperconnectivity predicted positive symptoms, especially delusions. This hyperconnectivity seems to be a prominent feature of paranoid schizophrenia and could represent the pathophysiological change underlying the psychopathology. The cross-sectional nature of our data means that causal associations are speculative. Nonetheless, our results suggest that hyperconnectivity within the SN could be a potential biomarker of schizophrenia. FundingJim Gatherall Travelling Fellowship awarded to RK to attend Stanford Cognitive and Systems Neuroscience laboratory.

Increased Functional Connectivity and Brain Atrophy in Elderly with Subjective Memory Complaints

Subjective memory complaints (SMC) are common among elderly. Although subtle changes in memory functioning can hardly be determined using neuropsychological evaluation, neuroimaging studies indicate regionally smaller brain structures in elderly with SMC. Imaging of resting-state functional connectivity is sensitive to detect changes in neurodegenerative diseases, but is currently underexplored in SMC. Here, we investigate resting-state functional connectivity and brain structure in SMC. We analyzed magnetic resonance imaging data of 25 elderly with SMC and 29 age-matched controls (mean age of 71 years). Voxel-based morphometry and volume measurements of subcortical structures were employed on the structural scans using FSL. The dual regression method was used to analyze voxel-wise functional connectivity in relation to eight well-characterized resting-state networks. Group differences were studied with two-sample t-tests (p<0.05, Family-Wise Error corrected). In addition to gray matter volume reductions (hippocampus, anterior cingulate cortex (ACC), medial prefrontal cortex, cuneus, precuneus, and precentral gyrus), elderly with SMC showed increased functional connectivity in the default mode network (hippocampus, thalamus, posterior cingulate cortex (PCC), cuneus, precuneus, and superior temporal gyrus) and the medial visual network (ACC, PCC, cuneus, and precuneus). This study is the first which demonstrates that, in addition to smaller regional brain volumes, increases in functional connectivity are present in elderly with SMC. This suggests that self-reported SMC is a reflection of objective alterations in brain function. Furthermore, our results indicate that functional imaging, in addition to structural imaging, can be a useful tool to objectively determine a difference in brain integrity in SMC.

Advances in simultaneous atmospheric profile and cloud parameter regression based retrieval from high‐spectral resolution radiance measurements

The dual‐regression (DR) method retrieves information about the Earth surface and vertical atmospheric conditions from measurements made by any high‐spectral resolution infrared sounder in space. The retrieved information includes temperature and atmospheric gases (such as water vapor, ozone, and carbon species) as well as surface and cloud top parameters. The algorithm was designed to produce a high‐quality product with low latency and has been demonstrated to yield accurate results in real‐time environments. The speed of the retrieval is achieved through linear regression, while accuracy is achieved through a series of classification schemes and decision‐making steps. These steps are necessary to account for the nonlinearity of hyperspectral retrievals. In this work, we detail the key steps that have been developed in the DR method to advance accuracy in the retrieval of nonlinear parameters, specifically cloud top pressure. The steps and their impact on retrieval results are discussed in‐depth and illustrated through relevant case studies. In addition to discussing and demonstrating advances made in addressing nonlinearity in a linear geophysical retrieval method, advances toward multi‐instrument geophysical analysis by applying the DR to three different operational sounders in polar orbit are also noted. For any area on the globe, the DR method achieves consistent accuracy and precision, making it potentially very valuable to both the meteorological and environmental user communities.

Reduced functional brain connectivity prior to and after disease onset in Huntington's disease

BackgroundHuntington's disease (HD) is characterised by both regional and generalised neuronal cell loss in the brain. Investigating functional brain connectivity patterns in rest in HD has the potential to broaden the understanding of brain functionality in relation to disease progression. This study aims to establish whether brain connectivity during rest is different in premanifest and manifest HD as compared to controls.MethodsAt the Leiden University Medical Centre study site of the TRACK-HD study, 20 early HD patients (disease stages 1 and 2), 28 premanifest gene carriers and 28 healthy controls underwent 3 T MRI scanning. Standard and high-resolution T1-weighted images and a resting state fMRI scan were acquired. Using FSL, group differences in resting state connectivity were examined for eight networks of interest using a dual regression method. With a voxelwise correction for localised atrophy, group differences in functional connectivity were examined.ResultsBrain connectivity of the left middle frontal and pre-central gyrus, and right post central gyrus with the medial visual network was reduced in premanifest and manifest HD as compared to controls (0.05 > p > 0.0001). In manifest HD connectivity of numerous widespread brain regions with the default mode network and the executive control network were reduced (0.05 > p > 0.0001).DiscussionBrain regions that show reduced intrinsic functional connectivity are present in premanifest gene carriers and to a much larger extent in manifest HD patients. These differences are present even when the potential influence of atrophy is taken into account. Resting state fMRI could potentially be used for early disease detection in the premanifest phase of HD and for monitoring of disease modifying compounds.

The impact of “physiological correction” on functional connectivity analysis of pharmacological resting state fMRI

Growing interest in pharmacological resting state fMRI (RSfMRI) necessitates developing standardized and robust analytical approaches that are insensitive to spurious correlated physiological signals. However, in pharmacological experiments physiological variations constitute an important aspect of the pharmacodynamic/pharmacokinetic profile of drug action; therefore retrospective corrective methods that discard physiological signals as noise may not be suitable. Previously, we have shown that template-based dual regression analysis is a sensitive method for model-free and objective detection of drug-specific effects on functional brain connectivity. In the current study, the robustness of this standard approach to physiological variations in a placebo controlled, repeated measures pharmacological RSfMRI study of morphine and alcohol in 12 healthy young men is tested. The impact of physiology-related variations on statistical inferences has been studied by: 1) modeling average physiological rates in higher level group analysis; 2) Regressing out the instantaneous respiration variation (RV); 3) applying retrospective image correction (RETROICOR) in the preprocessing stage; and 4) performing combined RV and heart rate correction (RVHRCOR) by regressing out physiological pulses convolved with canonical respiratory and cardiac hemodynamic response functions. Results indicate regional sensitivity of the BOLD signal to physiological variations, especially in the vicinity of large vessels, plus certain brain structures that are reported to be involved in physiological regulation, such as posterior cingulate, precuneus, medial prefrontal and insular cortices, as well as the thalamus, cerebellum and the brainstem. The largest impact of "correction" on final statistical test outcomes resulted from including the average respiration frequency and heart rate in the higher-level group analysis. Overall, the template-based dual regression method seems robust against physical noise that is corrected by RV regression or RETROICOR. However, convolving the RV and HR with canonical hemodynamic response functions caused a notable change in the BOLD signal variance, and in resting state connectivity estimates. The impact of RVHRCOR on statistical tests was limited to elimination of both morphine and alcohol effects related to the somatosensory network that consists of insula and cingulate cortex-important structures for autonomic regulation. Although our data do not warrant speculations about neuronal or vascular origins of these effects, these observations raise caution about the implications of physiological 'noise' and the risks of introducing false positives (e.g. increased white matter connectivity) by using generalized physiological correction methods in pharmacological studies. The obvious sensitivity of the posterior part of the default mode network to different correction schemes, underlines the importance of controlling for physiological fluctuations in seed-based functional connectivity analyses.

Dual-Regression Retrieval Algorithm for Real-Time Processing of Satellite Ultraspectral Radiances

AbstractA fast physically based dual-regression (DR) method is developed to produce, in real time, accurate profile and surface- and cloud-property retrievals from satellite ultraspectral radiances observed for both clear- and cloudy-sky conditions. The DR relies on using empirical orthogonal function (EOF) regression “clear trained” and “cloud trained” retrievals of surface skin temperature, surface-emissivity EOF coefficients, carbon dioxide concentration, cloud-top altitude, effective cloud optical depth, and atmospheric temperature, moisture, and ozone profiles above the cloud and below thin or broken cloud. The cloud-trained retrieval is obtained using cloud-height-classified statistical datasets. The result is a retrieval with an accuracy that is much higher than that associated with the retrieval produced by the unclassified regression method currently used in the International Moderate Resolution Imaging Spectroradiometer/Atmospheric Infrared Sounder (MODIS/AIRS) Processing Package (IMAPP) retrieval system. The improvement results from the fact that the nonlinear dependence of spectral radiance on the atmospheric variables, which is due to cloud altitude and associated atmospheric moisture concentration variations, is minimized as a result of the cloud-height-classification process. The detailed method and results from example applications of the DR retrieval algorithm are presented. The new DR method will be used to retrieve atmospheric profiles from Aqua AIRS, MetOp Infrared Atmospheric Sounding Interferometer, and the forthcoming Joint Polar Satellite System ultraspectral radiance data.

Resting-State Brain Networks in Type 1 Diabetic Patients With and Without Microangiopathy and Their Relation to Cognitive Functions and Disease Variables

Cognitive functioning depends on intact brain networks that can be assessed with functional magnetic resonance imaging (fMRI) techniques. We hypothesized that cognitive decrements in type 1 diabetes mellitus (T1DM) are associated with alterations in resting-state neural connectivity and that these changes vary according to the degree of microangiopathy. T1DM patients with (MA+: n = 49) and without (MA−: n = 52) microangiopathy were compared with 48 healthy control subjects. All completed a neuropsychological assessment and resting-state fMRI. Networks were identified using multisubject independent component analysis; specific group differences within each network were analyzed using the dual-regression method, corrected for confounding factors and multiple comparisons. Relative to control subjects, MA− patients showed increased connectivity in networks involved in motor and visual processes, whereas MA+ patients showed decreased connectivity in networks involving attention, working memory, auditory and language processing, and motor and visual processes. Better information-processing speed and general cognitive ability were related to increased degree of connectivity. T1DM is associated with a functional reorganization of neural networks that varies, dependent on the presence or absence of microangiopathy.

Whole brain resting-state analysis reveals decreased functional connectivity in major depression

Recently, both increases and decreases in resting-state functional connectivity have been found in major depression. However, these studies only assessed functional connectivity within a specific network or between a few regions of interest, while comorbidity and use of medication was not always controlled for. Therefore, the aim of the current study was to investigate whole-brain functional connectivity, unbiased by a priori definition of regions or networks of interest, in medication-free depressive patients without comorbidity. We analyzed resting-state fMRI data of 19 medication-free patients with a recent diagnosis of major depression (within 6 months before inclusion) and no comorbidity, and 19 age- and gender-matched controls. Independent component analysis was employed on the concatenated data sets of all participants. Thirteen functionally relevant networks were identified, describing the entire study sample. Next, individual representations of the networks were created using a dual regression method. Statistical inference was subsequently done on these spatial maps using voxel-wise permutation tests. Abnormal functional connectivity was found within three resting-state networks in depression: (1) decreased bilateral amygdala and left anterior insula connectivity in an affective network, (2) reduced connectivity of the left frontal pole in a network associated with attention and working memory, and (3) decreased bilateral lingual gyrus connectivity within ventromedial visual regions. None of these effects were associated with symptom severity or gray matter density. We found abnormal resting-state functional connectivity not previously associated with major depression, which might relate to abnormal affect regulation and mild cognitive deficits, both associated with the symptomatology of the disorder.

Experimental analysis of critical oxygen delivery

Systemic variables were evaluated with respect to O(2) delivery to test the hypothesis that critical O(2) delivery and critical Hb can be estimated by multiple variables collected simultaneously. Rats were subjected to transfusion with either fresh or stored blood and then subjected to stepwise isovolemic hemodilution. Critical levels were measured by the dual-regression method from plots of systemic variables against O(2) delivery and Hb. Delivery was calculated from cardiac index and arterial O(2) content. We found that 1) after hemodilution, O(2) delivery changed in a nonlinear relationship with Hb; 2) critical delivery calculated using 30 different systemic variables was not statistically different from each other; 3) critical delivery and critical Hb were correlated but were not different between animals receiving fresh or stored blood; and 4) similar critical levels were found using a single variable from several animals and using several variables from the same subject. The best variables to estimate critical delivery were lactate, bicarbonate, base excess, O(2) extraction ratio, expired CO(2), pulse pressure, cardiac index, and systolic pressure. The data suggest that a multivariable analysis of critical delivery may help determine the physiological oxygenation boundary at the whole body level. This may assist in finding therapeutic triggers on an individual basis using systemic markers of the transition from aerobic to anaerobic metabolism.