Neuromark PET: A multivariate method for Estimating and comparing whole brain functional networks and connectomes from fMRI and PET data.

Positron emission tomography (PET) and magnetic resonance imaging (MRI) are both widely used neuroimaging techniques to study brain function. Although whole brain resting functional MRI (fMRI) connectomes are widely used, the integration or association of whole brain functional connectomes with PET data are rarely done. This likely stems from the fact that PET data is typically analyzed by using a regions of interest approach, while whole brain spatial networks and their connectivity (covariation) receive much less attention. As a result, to date, there have been no direct comparisons between whole brain PET and fMRI connectomes. In this study, we present a method that uses spatially constrained independent component analysis (scICA) to estimate corresponding PET and fMRI connectomes and examine the relationship between them using mild cognitive impairment (MCI) datasets. Our results demonstrate highly modularized PET connectome patterns that complement those identified from resting fMRI. In particular, fMRI showed strong intra-domain connectivity with interdomain anticorrelation in sensorimotor and visual domains as well as default mode network. PET amyloid data showed similar strong intra-domain effects, but showed much higher correlations within cognitive control and default mode domains, as well as anticorrelation between cerebellum and other domains. The estimated PET networks have similar, but not identical, network spatial patterns to the resting fMRI networks, with the PET networks being slightly smoother and, in some cases, showing variations in subnodes. We also analyzed the differences between individuals with MCI receiving medication versus a placebo. Results show both common and modality specific treatment effects on fMRI and PET connectomes. From our fMRI analysis, we observed higher activation differences in various regions, such as the connection between the thalamus and middle occipital gyrus, as well as the insula and right middle occipital gyrus. Meanwhile, the PET analysis revealed increased activation between the anterior cingulate cortex and the left inferior parietal lobe, along with other regions, in individuals who received medication versus placebo. In sum, our novel approach identifies corresponding whole-brain PET and fMRI networks and connectomes. While we observed common patterns of network connectivity, our analysis of the MCI treatment and placebo groups revealed that each modality identifies a unique set of networks, highlighting differences between the two groups.

A Multivariate Method for Estimating and comparing whole brain functional connectomes from fMRI and PET data.

Positron emission tomography (PET) and magnetic resonance imaging (MRI) are two commonly used imaging techniques to visualize brain function. The use of inter-network covariation (a functional connectome) is a widely used approach to infer links among different brain networks. While whole brain resting fMRI connectomes are widely used, PET data has mostly been analyzed using a few regions of interest. There has been much less work estimating PET spatial networks and almost no work on their connectivity (covariation) in the context of a whole brain data-driven connectome, nor have there been direct comparisons between whole brain PET and fMRI connectomes. Here we present an approach to leverage spatially constrained ICA to compute an estimate of the PET connectome. Results reveal highly modularized connectome patterns that are complementary to that identified from resting fMRI. Similarly, we were able to identify comparable resting networks from a PiB PET scan that can be directly compared to networks in rest fMRI data and results reveal similar, but not identical, network spatial patterns, with the PET networks being slightly smoother and, in some cases, showing variations in subnodes. The resulting networks, decomposed into spatial maps and subject expressions (loading parameters) linked to resting fMRI provide a new way to evaluate the complementary information in PET and fMRI and open up new possibilities for biomarker development.Clinical Relevance-This study analyzes the whole-brain PET and fMRI connectomes, capturing the complementary information from both imaging modalities, thereby introducing a new scope for biomarker development.

BrainForge: an online data analysis platform for integrative neuroimaging acquisition, analysis, and sharing.

BrainForge is a cloud-enabled, web-based analysis platform for neuroimaging research. This website allows users to archive data from a study and effortlessly process data on a high-performance computing cluster. After analyses are completed, results can be quickly shared with colleagues. BrainForge solves multiple problems for researchers who want to analyze neuroimaging data, including issues related to software, reproducibility, computational resources, and data sharing. BrainForge can currently process structural, functional, diffusion, and arterial spin labeling MRI modalities, including preprocessing and group level analyses. Additional pipelines are currently being added, and the pipelines can accept the BIDS format. Analyses are conducted completely inside of Singularity containers and utilize popular software packages including Nipype, Statistical Parametric Mapping, the Group ICA of fMRI Toolbox, and FreeSurfer. BrainForge also features several interfaces for group analysis, including a fully automated adaptive ICA approach.

Safety and biomarker effects of candesartan in non-hypertensive adults with prodromal Alzheimer's disease.

Observational studies suggest that angiotensin receptor blockers in hypertensive adults are associated with lower post-mortem indicators of Alzheimer's disease pathology. Candesartan, an angiotensin receptor blocker, has a positive cognitive effect in mild cognitive impairment with hypertension. However, its safety and effects in non-hypertensive individuals with Alzheimer's disease are unclear. This is the first double-blind randomized placebo-controlled trial aimed to assess safety and effects of 1-year therapy of candesartan on biomarkers and clinical indicators of Alzheimer's disease in non-hypertensive individuals with biomarker-confirmed prodromal Alzheimer's disease. Seventy-seven non-hypertensive participants 50 years or older (mean age: 68.1 years; 62% women; 20% African American) with mild cognitive impairment and biomarker confirmed Alzheimer's disease were randomized to escalating doses of once daily oral candesartan (up to 32 mg) or matched placebo. Main outcomes included safety and tolerability of candesartan, cerebrospinal fluid biomarkers (amyloid-ß42, amyloid-ß40, total tau and phospho-tau). Additional exploratory outcomes included PET imaging (Pittsburgh Compound-B (11C-PiB) and 18F-flortaucipir), brain MRI (structural and connectivity measures) and cognitive functioning. Analyses used intention-to-treat approach with group comparisons of safety measures using Chi-square test, and repeated measures mixed effects models were used to assess candesartan effects on main and exploratory outcomes (ClinicalTrials.gov, NCT02646982). Candesartan was found to be safe with no significant difference in safety measures: symptoms of hypotension, renal failure or hyperkalemia. Candesartan was also found to be associated with increases in cerebrospinal fluid Aß40 (between-group mean difference: 1211.95 pg/ml, 95% confidence interval: 313.27, 2110.63) and Aß42 (49.51 pg/ml, 95% confidence interval: -98.05, -0.98) reflecting lower brain amyloid accumulation. Candesartan was associated with decreased 11C-PiB in the parahippocampal region (-0.1104, 95% confidence interval: -0.19, -0.029) which remained significant after false discovery rate correction, and with an increase in functional network connectivity in the subcortical networks. Candesartan was further associated with improved executive function (Trail Making Test Part B) performance (-11.41 s, 95% confidence interval: -11.94, -10.89) and trended for an improved global cognitive functioning reflected by a composite cognitive score (0.002, 95% confidence interval: -0.0002, 0.005). We did not observe significant effects on tau levels, hippocampal volume or other cognitive measures (memory or clinical dementia rating scale-sum of boxes). In conclusion, among non-hypertensive prodromal Alzheimer's disease, candesartan is safe and likely decreases brain amyloid biomarkers, enhances subcortical brain connectivity and has favourable cognitive effects. These findings suggest that candesartan may have an important therapeutic role in Alzheimer's disease, and warrant further investigation given the lack of clear treatment options for this devastating illness.

Percutaneous electric nerve field stimulation alters cortical thickness in a pilot study of veterans with fibromyalgia.

Objective: To evaluate changes in cortical thickness and right posterior insula (r-pIns) gamma-aminobutyric acid (GABA) concentrations in veterans with fibromyalgia treated with auricular percutaneous electric nerve field stimulation (PENFS). Materials & methods: This was a randomized, controlled, open label investigation conducted in a government hospital. Twenty-one veterans with fibromyalgia were randomized to receive either standard therapy (ST; i.e., 4 weekly visits with a pain practitioner) or ST with auricular PENFS (ST + PENFS). Neuroimaging data was collected at baseline (i.e. before the first treatment session) and again within 2 weeks post-treatment.​ Clinical pain and physical function were also assessed at these timepoints. Single-voxel magnetic resonance spectroscopy was carried out in r-pIns to assess changes in r-pIns GABA concentrations and high-resolution T1-weighted images were collected to assess changes in regional gray matter volume using cortical thickness. Results: Both the ST + PENFS and ST groups reported a decrease in pain with treatment. Volumetric: Cortical thickness significantly decreased in the left middle posterior cingulate (p = 0.018) and increased in the left cuneus (p = 0.014) following ST + PENFS treatment. These findings were significant following FDR correction for multiple comparisons. ST group right hemisphere insula cortical thickness increased post-treatment and was significantly (p = 0.02) inversely correlated with pain scores. ST + PENFS group right hemisphere posterior dorsal cingulate size significantly (p = 0.044) positively correlated with pain scores. GABA: There were no significant correlations with GABA, though a trend was noted towards increased GABA following treatment in both groups (p = 0.083) using a linear mixed effects model. Conclusions: Results suggest a novel effect of PENFS reflected by differential volumetric changes compared to ST. The changes in GABA that occur in both groups are more likely related to ST. Insular GABA and cortical thickness in key regions of interest may be developed as potential biomarkers for evaluating chronic pain pathology and treatment outcomes.

Frontal Metabolites and Alzheimer's Disease Biomarkers in Healthy Older Women and Women Diagnosed with Mild Cognitive Impairment.

BACKGROUND: Women account for two thirds of the prevalence and incidence of Alzheimer's disease (AD) and mild cognitive impairment (MCI). Evidence suggest that sex may differently influence the expression of proteins amyloid-beta (Aß1-42) and tau, for which early detection is crucial in prevention of the disease. OBJECTIVE: We investigated the effect of aging and cerebrospinal fluid (CSF) levels of Aß1-42 and tau on frontal metabolites measured with proton magnetic resonance spectroscopy (MRS) in a cohort of cognitively normal older women and women with MCI. METHODS: 3T single-voxel MRS was performed on the medial frontal cortex, using Point Resolved Spectroscopy (PRESS) and Mescher-Garwood Point Resolved Spectroscopy (MEGA-PRESS) in 120 women (age range 50-85). CSF samples of Aß1-42 and tau and scores of general cognition were also obtained. RESULTS: Levels of frontal gamma aminobutyric acid (GABA+) were predicted by age, independently of disease and CSF biomarkers. Importantly, levels of GABA+ were reduced in MCI patients. Additionally, we found that levels of N-acetylaspartate relative to myo-inositol (tNAA/mI) predicted cognition in MCI patients only and were not related to CSF biomarkers. CONCLUSION: This study is the first to demonstrate a strong association between frontal GABA+ levels and neurological aging in a sample consisting exclusively of healthy older women with various levels of CSF tau and Aß1-42 and women with MCI. Importantly, our results show no correlation between CSF biomarkers and MRS metabolites in this sample.

Relationships between frontal metabolites and Alzheimer's disease biomarkers in cognitively normal older adults.

Elevated expression of ß-amyloid (Aß1-42) and tau are considered risk-factors for Alzheimer's disease in healthy older adults. We investigated the effect of aging and cerebrospinal fluid levels of Aß1-42 and tau on 1) frontal metabolites measured with proton magnetic resonance spectroscopy (MRS) and 2) cognition in cognitively normal older adults (n = 144; age range 50-85). Levels of frontal gamma aminobutyric acid (GABA+) and myo-inositol relative to creatine (mI/tCr) were predicted by age. Levels of GABA+ predicted cognitive performance better than mI/tCr. Additionally, we found that frontal levels of n-acetylaspartate relative to creatine (tNAA/tCr) were predicted by levels of t-tau. In cognitively normal older adults, levels of frontal GABA+ and mI/tCr are predicted by aging, with levels of GABA+ decreasing with age and the opposite for mI/tCr. These results suggest that age- and biomarker-related changes in brain metabolites are not only located in the posterior cortex as suggested by previous studies and further demonstrate that MRS is a viable tool in the study of aging and biomarkers associated with pathological aging and Alzheimer's disease.

Temporal lobe epilepsy affects spatial organization of entorhinal cortex connectivity.

Evidence for structural connectivity patterns within the medial temporal lobe derives primarily from postmortem histological studies. In humans and nonhuman primates, the parahippocampal gyrus (PHg) is subdivided into parahippocampal (PHc) and perirhinal (PRc) cortices, which receive input from distinct cortical networks. Likewise, their efferent projections to the entorhinal cortex (ERc) are distinct. The PHc projects primarily to the medial ERc (M-ERc). The PRc projects primarily to the lateral portion of the ERc (L-ERc). Both M-ERc and L-ERc, via the perforant pathway, project to the dentate gyrus and hippocampal (HC) subfields. Until recently, these neural circuits could not be visualized in vivo. Diffusion tensor imaging algorithms have been developed to segment gray matter structures based on probabilistic connectivity patterns. However, these algorithms have not yet been applied to investigate connectivity in the temporal lobe or changes in connectivity architecture related to disease processes. In this study, this segmentation procedure was used to classify ERc gray matter based on PRc, ERc, and HC connectivity patterns in 7 patients with temporal lobe epilepsy (TLE) without hippocampal sclerosis (mean age, 14.86 ±â€¯3.34 years) and 7 healthy controls (mean age, 23.86 ±â€¯2.97 years). Within samples paired t-tests allowed for comparison of ERc connectivity between epileptogenic and contralateral hemispheres. In healthy controls, there were no significant within-group differences in surface area, volume, or cluster number of ERc connectivity-defined regions (CDR). Likewise, in line with histology results, ERc CDR in the control group were well-organized, uniform, and segregated via PRc/PHc afferent and HC efferent connections. Conversely, in TLE, there were significantly more PRc and HC CDR clusters in the epileptogenic than the contralateral hemisphere. The surface area of the PRc CDR was greater, and that of the HC CDRs was smaller, in the epileptogenic hemisphere as well. Further, there was no clear delineation between M-ERc and L-ERc connectivity with PRc, PHc or HC in TLE. These results suggest a breakdown of the spatial organization of PHg-ERc-HC connectivity in TLE. Whether this breakdown is the cause or result of epileptic activity remains an exciting research question.

Broca's area - thalamic connectivity.

Broca's area is crucially involved in language processing. The sub-regions of Broca's area (pars triangularis, pars opercularis) presumably are connected via corticocortical pathways. However, growing evidence suggests that the thalamus may also be involved in language and share some of the linguistic functions supported by Broca's area. Functional connectivity is thought to be achieved via corticothalamic/thalamocortical white matter pathways. Our study investigates structural connectivity between Broca's area and the thalamus, specifically ventral anterior nucleus and pulvinar. We demonstrate that Broca's area shares direct connections with these thalamic nuclei and suggest a local Broca's area-thalamus network potentially involved in linguistic processing. Thalamic connectivity with Broca's area may serve to selectively recruit cortical regions storing multimodal features of lexical items and to bind them together during lexical-semantic processing. In addition, Broca's area-thalamic circuitry may enable cortico-thalamo-cortical information transfer and modulation between BA 44 and 45 during language comprehension and production.