Effect of Meditation on Brain Activity during an Attention Task: A Comparison Study of ASL and BOLD Task fMRI.

Focused attention meditation (FAM) training has been shown to improve attention, but the neural basis of FAM on attention has not been thoroughly understood. Here, we aim to investigate the neural effect of a 2-month FAM training on novice meditators in a visual oddball task (a frequently adopted task to evaluate attention), evaluated with both ASL and BOLD fMRI. Using ASL, activation was increased in the middle cingulate (part of the salience network, SN) and temporoparietal (part of the frontoparietal network, FPN) regions; the FAM practice time was negatively associated with the longitudinal changes in activation in the medial prefrontal (part of the default mode network, DMN) and middle frontal (part of the FPN) regions. Using BOLD, the FAM practice time was positively associated with the longitudinal changes of activation in the inferior parietal (part of the dorsal attention network, DAN), dorsolateral prefrontal (part of the FPN), and precentral (part of the DAN) regions. The effect sizes for the activation changes and their association with practice time using ASL are significantly larger than those using BOLD. Our study suggests that FAM training may improve attention via modulation of the DMN, DAN, SN, and FPN, and ASL may be a sensitive tool to study the FAM effect on attention.

Global Functional Connectivity at Rest Is Associated with Attention: An Arterial Spin Labeling Study.

Neural markers of attention, including those frequently linked to the event-related potential P3 (P300) or P3b component, vary widely within and across participants. Understanding the neural mechanisms of attention that contribute to the P3 is crucial for better understanding attention-related brain disorders. All ten participants were scanned twice with a resting-state PCASL perfusion MRI and an ERP with a visual oddball task to measure brain resting-state functional connectivity (rsFC) and P3 parameters (P3 amplitudes and P3 latencies). Global rsFC (average rsFC across the entire brain) was associated with both P3 amplitudes (r = 0.57, p = 0.011) and P3 onset latencies (r = -0.56, p = 0.012). The observed P3 parameters were correlated with predicted P3 amplitude from the global rsFC (amplitude: r = +0.48, p = 0.037; latency: r = +0.40, p = 0.088) but not correlated with the rsFC over the most significant individual edge. P3 onset latency was primarily related to long-range connections between the prefrontal and parietal/limbic regions, while P3 amplitudes were related to connections between prefrontal and parietal/occipital, between sensorimotor and subcortical, and between limbic/subcortical and parietal/occipital regions. These results demonstrated the power of resting-state PCASL and P3 correlation with brain global functional connectivity.

Pattern of Altered Magnetization Transfer Rate in Alzheimer's Disease.

BACKGROUND: Biomarkers for Alzheimer's disease (AD) are crucial for early diagnosis and treatment monitoring once disease modifying therapies become available. OBJECTIVE: This study aims to quantify the forward magnetization transfer rate (kfor) map from brain tissue water to macromolecular protons and use it to identify the brain regions with abnormal kfor in AD and AD progression. METHODS: From the Cardiovascular Health Study (CHS) cognition study, magnetization transfer imaging (MTI) was acquired at baseline from 63 participants, including 20 normal controls (NC), 18 with mild cognitive impairment (MCI), and 25 AD subjects. Of those, 53 participants completed a follow-up MRI scan and were divided into four groups: 15 stable NC, 12 NC-to-MCI, 12 stable MCI, and 14 MCI/AD-to-AD subjects. kfor maps were compared across NC, MCI, and AD groups at baseline for the cross-sectional study and across four longitudinal groups for the longitudinal study. RESULTS: We found a lower kfor in the frontal gray matter (GM), parietal GM, frontal corona radiata (CR) white matter (WM) tracts, frontal and parietal superior longitudinal fasciculus (SLF) WM tracts in AD relative to both NC and MCI. Further, we observed progressive decreases of kfor in the frontal GM, parietal GM, frontal and parietal CR WM tracts, and parietal SLF WM tracts in stable MCI. In the parietal GM, parietal CR WM tracts, and parietal SLF WM tracts, we found trend differences between MCI/AD-to-AD and stable NC. CONCLUSION: Forward magnetization transfer rate is a promising biomarker for AD diagnosis and progression.

The Longitudinal Effect of Meditation on Resting-State Functional Connectivity Using Dynamic Arterial Spin Labeling: A Feasibility Study.

We aimed to assess whether dynamic arterial spin labeling (dASL), a novel quantitative MRI technique with minimal contamination of subject motion and physiological noises, could detect the longitudinal effect of focused attention meditation (FAM) on resting-state functional connectivity (rsFC). A total of 10 novice meditators who recorded their FAM practice time were scanned at baseline and at the 2-month follow-up. Two-month meditation practice caused significantly increased rsFC between the left medial temporal (LMT) seed and precuneus area and between the right frontal eye (RFE) seed and medial prefrontal cortex. Meditation practice time was found to be positively associated with longitudinal changes of rsFC between the default mode network (DMN) and dorsal attention network (DAN), between DMN and insula, and between DAN and the frontoparietal control network (FPN) but negatively associated with changes of rsFC between DMN and FPN, and between DAN and visual regions. These findings demonstrate the capability of dASL in identifying the FAM-induced rsFC changes and suggest that the practice of FAM can strengthen the efficient control of FPN on fast switching between DMN and DAN and enhance the utilization of attentional resources with reduced focus on visual processing.

Longitudinal effects of meditation on brain resting-state functional connectivity.

Changes in brain resting-state functional connectivity (rsFC) were investigated using a longitudinal design by following a 2-month focused attention meditation (FAM) practice and analyzing their association with FAM practice time. Ten novice meditators were recruited from a university meditation course. Participants were scanned with a resting-state fMRI sequence with multi-echo EPI acquisition at baseline and at the 2-month follow-up. Total FAM practice time was calculated from the daily log of the participants. We observed significantly increased rsFC between the posterior cingulate cortex (PCC) and dorsal attention network (DAN), the right middle temporal (RMT) region and default mode network (DMN), the left and right superior parietal lobules (LSPL/RSPL) and DMN, and the LSPL/RSPL and DAN. Furthermore, the rsFC between the LSPL and medial prefrontal cortex was significantly associated with the FAM practice time. These results demonstrate increased connectivity within the DAN, between the DMN and DAN, and between the DMN and visual cortex. These findings demonstrate that FAM can enhance the brain connection among and within brain networks, especially DMN and DAN, indicating potential effect of FAM on fast switching between mind wandering and focused attention and maintaining attention once in the attentive state.

Cerebral Blood Flow Predicts Conversion of Mild Cognitive Impairment into Alzheimer's Disease and Cognitive Decline: An Arterial Spin Labeling Follow-up Study.

BACKGROUND: This is the first longitudinal study to assess regional cerebral blood flow (rCBF) changes during the progression from normal control (NC) through mild cognitive impairment (MCI) and Alzheimer's disease (AD). OBJECTIVE: We aim to determine if perfusion MRI biomarkers, derived from our prior cross-sectional study, can predict the onset and cognitive decline of AD. METHODS: Perfusion MRIs using arterial spin labeling (ASL) were acquired in 15 stable-NC, 14 NC-to-MCI, 16 stable-MCI, and 18 MCI/AD-to-AD participants from the Cardiovascular Health Study (CHS) cognition study. Group comparisons, predictions of AD conversion and time to conversion, and Modified Mini-Mental State Examination (3MSE) from rCBF were performed. RESULTS: Compared to the stable-NC group: 1) the stable-MCI group exhibited rCBF decreases in the right temporoparietal (p = 0.00010) and right inferior frontal and insula (p = 0.0094) regions; and 2) the MCI/AD-to-AD group exhibited rCBF decreases in the bilateral temporoparietal regions (p = 0.00062 and 0.0035). Compared to the NC-to-MCI group, the stable-MCI group exhibited a rCBF decrease in the right hippocampus region (p = 0.0053). The baseline rCBF values in the posterior cingulate cortex (PCC) (p = 0.0043), bilateral superior medial frontal regions (BSMF) (p = 0.012), and left inferior frontal (p = 0.010) regions predicted the 3MSE scores for all the participants at follow-up. The baseline rCBF in the PCC and BSMF regions predicted the conversion and time to conversion from MCI to AD (p < 0.05; not significant after multiple corrections). CONCLUSION: We demonstrated the feasibility of ASL in detecting rCBF changes in the typical AD-affected regions and the predictive value of baseline rCBF on AD conversion and cognitive decline.

Cerebral Blood Flow Is Associated with Diagnostic Class and Cognitive Decline in Alzheimer's Disease.

BACKGROUND: Reliable cerebral blood flow (CBF) biomarkers using a noninvasive imaging technique are sought to facilitate early diagnosis and intervention in early Alzheimer's disease (AD). OBJECTIVE: We aim to identify brain regions in which CBF values are affected and related to cognitive decline in early AD using a large cohort. METHODS: Perfusion MRIs using continuous arterial spin labeling were acquired at 1.5 T in 58 normal controls (NC), 50 mild cognitive impairments (MCI), and 40 AD subjects from the Cardiovascular Health Study Cognition Study. Regional absolute CBF and normalized CBF (nCBF) values, without and with correction of partial volume effects, were compared across three groups. Association between regional CBF values and Modified Mini-Mental State Examination (3MSE) were investigated by multiple linear regression analyses adjusted for cardiovascular risk factors. RESULTS: After correcting for partial volume effects and cardiovascular risk factors, ADs exhibited decreased nCBF with the strongest reduction in the bilateral posterior cingulate & precuneus region (p < 0.001) compared to NCs, and the strongest reduction in the bilateral superior medial frontal region (p < 0.001) compared to MCIs. MCIs exhibited the strongest nCBF decrease in the left hippocampus and nCBF increase in the right inferior frontal and insular region. The 3MSE scores within the symptomatic subjects were significantly associated with nCBF in the bilateral posterior and middle cingulate and parietal (p < 0.001), bilateral superior medial frontal (p < 0.001), bilateral temporoparietal (p < 0.02), and right hippocampus (p = 0.02) regions. CONCLUSION: Noninvasive perfusion MRI can detect functional changes across diagnostic class and serve as a staging biomarker of cognitive status.

Abnormal perfusion fluctuation and perfusion connectivity in bipolar disorder measured by dynamic arterial spin labeling.

OBJECTIVES: We sought to evaluate whether dynamic Arterial Spin Labeling (dASL), a novel quantitative technique robust to artifacts and noise that especially arise in inferior brain regions, could characterize neural substrates of BD pathology and symptoms. METHODS: Forty-five subjects (19 BD patients, 26 controls) were imaged using a dASL sequence. Maps of average perfusion, perfusion fluctuation, and perfusion connectivity with anterior cingulate cortex (ACC) were derived. Patient symptoms were quantified along four symptom dimensions determined using factor analysis of the subjects from the Bipolar and Schizophrenia Network on Intermediate Phenotypes (BSNIP) study. Maps of the perfusion measures were compared between BD patients and controls and correlated with the symptom dimensions in the BD patients only by voxel-level and region-level analyses. RESULTS: BD patients exhibited (i) significantly increased perfusion fluctuations in the left fusiform and inferior temporal regions (P = .020, voxel-level corrected) and marginally increased perfusion fluctuations in the right temporal pole and inferior temporal regions (P = .063, cluster-level corrected), (ii) significantly increased perfusion connectivity between ACC and the occipitoparietal cortex (P = .050, cluster-level corrected). In BD patients, positive symptoms were negatively associated with ACC perfusion connectivity to the right orbitofrontal and superior frontal regions (P = .002, cluster-level corrected) and right orbitofrontal and inferior frontal regions (P = .023, cluster-level corrected). CONCLUSION: The abnormal perfusion fluctuations and connectivity alterations may underlie the mood fluctuations and cognitive and emotional dysregulation that characterize BD.

Improved perfusion pattern score association with type 2 diabetes severity using machine learning pipeline: Pilot study.

BACKGROUND: Type 2 diabetes mellitus (T2DM) is associated with alterations in the blood-brain barrier, neuronal damage, and arterial stiffness, thus affecting cerebral metabolism and perfusion. There is a need to implement machine-learning methodologies to identify a T2DM-related perfusion pattern and possible relationship between the pattern and cognitive performance/disease severity. PURPOSE: To develop a machine-learning pipeline to investigate the method's discriminative value between T2DM patients and normal controls, the T2DM-related network pattern, and association of the pattern with cognitive performance/disease severity. STUDY TYPE: A cross-sectional study and prospective longitudinal study with a 2-year time interval. POPULATION: Seventy-three subjects (41 T2DM patients and 32 controls) aged 50-85 years old at baseline, and 42 subjects (19 T2DM and 23 controls) aged 53-88 years old at 2-year follow-up. FIELD STRENGTH/SEQUENCE: 3T pseudocontinuous arterial spin-labeling MRI. ASSESSMENT: Machine-learning-based pipeline (principal component analysis, feature selection, and logistic regression classifier) to generate the T2DM-related network pattern and the individual scores associated with the pattern. STATISTICAL TESTS: Linear regression analysis with gray matter volume and education years as covariates. RESULTS: The machine-learning-based method is superior to the widely used univariate group comparison method with increased test accuracy, test area under the curve, test positive predictive value, adjusted McFadden's R square of 4%, 12%, 7%, and 24%, respectively. The pattern-related individual scores are associated with diabetes severity variables, mobility, and cognitive performance at baseline (P < 0.05, |r| > 0.3). More important, the longitudinal change of individual pattern scores is associated with the longitudinal change of HbA1c (P = 0.0053, r = 0.64), and baseline cholesterol (P = 0.037, r = 0.51). DATA CONCLUSION: The individual perfusion diabetes pattern score is a highly promising perfusion imaging biomarker for tracing the disease progression of individual T2DM patients. Further validation is needed from a larger study. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;49:834-844.

Fluorescent and colorimetric dual-mode aptasensor for thrombin detection based on target-induced conjunction of split aptamer fragments.

Since the lack of detection diversity of the single-signal readout strategy, it is urgent to develop fast and multisignal assay strategies. A highly selective and sensitive assay method with colorimetric and fluorometric dual signals readouts is presented in this paper. It is based on the principle that the target induced conjunction of split aptamer fragments assembled on the surface of Au nanoparticles (AuNPs). In the presence of targets, the color of solution changed from wine red to blue and can be measured both visual inspection and spectrophotometry because of the aggregation of AuNPs. At the same time, the report probes which are original hybrid with the anchoring aptamer fragments on the AuNPs surface can be released and recovers the fluorescence. By use of this detection strategy, the limit of detection for thrombin (TMB), as a model of analyte, were 0.45 and 0.16nM, respectively. Furthermore, this protocol can discriminate TMB from other analogue with high selectivity and can be used to detect TMB in human serum samples. The results came from the two signals were well consistent with each other, which demonstrated that it has application potential for detection of TMB in complex matrix.

A label-free, versatile and low-background chemiluminescence aptasensing strategy based on gold nanocluster catalysis combined with the separation of magnetic beads.

A label-free, versatile and low-background chemiluminescence (CL) sensing strategy based on gold nanocluster catalysis combined with the separation of magnetic beads (MBs) was developed. Kanamycin was selected as the target analyte to exhibit the analytical performance of this platform. Two single-stranded DNA (named DNA1 and DNA2) are ingeniously designed. DNA1, containing an aptamer sequence of the targets, was firstly immobilized on the MBs which were modified with many amino groups by amidation reaction. DNA2 consists of 30 repeat adenosine bases (A30) at the 5' terminal which were used to prepare AuNCs by a UV-light-assisted method and a 12 nucleotide sequence at the 3' terminal which can easily hybridize with DNA1 to form a partly complementary double-stranded structure. In the presence of targets, the aptamer modified on MBs would combine with targets and lead to release the prepared DNA-templated AuNCs. After the magnetic separation, enrichment AuNCs in the supernatant can catalyze the CL substrate to produce a strong CL signal. The well-designed CL sensing strategy exhibited a low detection limit of 0.035 nM for kanamycin, and it also showed good selectivity and stability. Most importantly, different targets can be analyzed only by changing the aptamer sequence that is immobilized on the MBs. Therefore, the strategy we proposed here has provided a versatile sensing platform for sensitively detecting various biomolecules at low levels.

Paper-based fluorescent sensor via aggregation induced emission fluorogen for facile and sensitive visual detection of hydrogen peroxide and glucose.

Hydrogen peroxide (H2O2), an important reactive oxygen species (ROS), is related to the oxidative stress in organisms, and plays important roles in a variety of cellular activities as well. So it is of crucial importance to develop sensitive and accurate sensing strategies to detect H2O2 in biological systems. Herein, by taking advantage of the unique emission characteristics of aggregation induced emission (AIE) fluorogens, we proposed a non-enzymatic fluorescence platform for facile and sensitive detection of H2O2, both in solution state using fluorescence spectrometer and on paper-based sensor via visual inspection. Through the reaction between L-cysteine and H2O2, the fluorescence of TPE-M-L, an AIE fluorogen formed between maleimide-functionalized tetraphenylethene (TPE-M) and L-cysteine, is quenched, and highly sensitive non-enzymatic H2O2 assay is readily carried out. The limit of detection (LOD) of 10nM in solution state and 2.5µM on paper-based sensor were obtained for H2O2 detection, which were superior or comparable to those previously reported in literature. Moreover, by integrating glucose oxidase with the AIE fluorogen of TPE-M-L, highly sensitive and selective glucose detection was also conveniently achieved both in solution state and on paper-based sensor by the as-proposed strategy, with the LODs of 50nM in solution state and 10µM via visual observation, much better than those obtained by other fluorescence methods. The as-proposed sensing strategy was also successfully applied to assay glucose in human serum samples. Therefore, the paper-based fluorescence sensor exhibits the advantages of simple fabrication, high sensitivity and portability, and has great potential to be applied in on-site assay of H2O2 and glucose in real samples.

The resting perfusion pattern associates with functional decline in type 2 diabetes.

We investigated the relationships between cerebral blood flow (CBF), cognitive, and mobility decline in type 2 diabetes mellitus (T2DM) over a 2-year period. Seventy-three participants (41 T2DM and 32 controls) were evaluated using volumetric CBF with arterial spin labeling perfusion magnetic resonance imaging at baseline and at the 2-year follow-up. Regions with significant CBF differences between T2DM participants and controls at baseline were detected using voxel-wise analysis. Correlation analysis was performed to investigate the association between regional CBF and cognitive or mobility performance over the 2-year span. Compared to controls, participants with T2DM had decreased CBF in the resting-state default mode, visual, and cerebellum networks. Greater decrease in longitudinal CBF values at these regions over a 2-year span was associated with worse gait, memory and executive functions, and higher baseline insulin resistance and worse baseline cognitive performance. In T2DM, impairment of resting regional perfusion is closely related to worse cognitive and mobility performance. Insulin resistance may further contribute to regional perfusion deficit in T2DM.