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The semi-adiabatic localization by adiabatic selective refocusing (sLASER) sequence provides single-shot full intensity signal with clean localization and minimal chemical shift displacement error and was recommended by the international MRS Consensus Group as the preferred localization sequence at high- and ultra-high fields. Across-vendor standardization of the sLASER sequence at 3 tesla has been challenging due to the B 1 requirements of the adiabatic inversion pulses and maximum B 1 limitations on some platforms. The aims of this study were to design a short-echo sLASER sequence that can be executed within a B 1 limit of 15 μT by taking advantage of gradient-modulated RF pulses, to implement it on three major platforms and to evaluate the between-vendor reproducibility of its perfomance with phantoms and in vivo. In addition, voxel-based first and second order B 0 shimming and voxel-based B 1 adjustments of RF pulses were implemented on all platforms. Amongst the gradient-modulated pulses considered (GOIA, FOCI and BASSI), GOIA-WURST was identified as the optimal refocusing pulse that provides good voxel selection within a maximum B 1 of 15 μT based on localization efficiency, contamination error and ripple artifacts of the inversion profile. An sLASER sequence (30 ms echo time) that incorporates VAPOR water suppression and 3D outer volume suppression was implemented with identical parameters (RF pulse type and duration, spoiler gradients and inter-pulse delays) on GE, Philips and Siemens and generated identical spectra on the GE 'Braino' phantom between vendors. High-quality spectra were consistently obtained in multiple regions (cerebellar white matter, hippocampus, pons, posterior cingulate cortex and putamen) in the human brain across vendors (5 subjects scanned per vendor per region; mean signal-to-noise ratio > 33; mean water linewidth between 6.5 Hz to 11.4 Hz). The harmonized sLASER protocol is expected to produce high reproducibility of MRS across sites thereby allowing large multi-site studies with clinical cohorts., (© 2019 John Wiley & Sons, Ltd.)

Neural activation patterns in the ventral visual cortex in response to different categories of visual stimuli (e.g., faces vs. houses) are less selective, or distinctive, in older adults than in younger adults, a phenomenon known as age-related neural dedifferentiation. In this study, we investigated whether neural dedifferentiation extends to the auditory cortex. Inspired by previous animal work, we also investigated whether individual differences in GABA are associated with individual differences in neural distinctiveness in humans. 20 healthy young adults (ages 18-29) and 23 healthy older adults (over 65) completed a functional magnetic resonance imaging (fMRI) scan, during which neural activity was estimated while they listened to music and foreign speech. GABA levels in the auditory, ventrovisual and sensorimotor cortex were estimated in the same individuals in a separate magnetic resonance spectroscopy (MRS) scan. Relative to the younger adults, the older adults exhibited both (1) less distinct activation patterns for music vs. speech stimuli and (2) lower GABA levels in the auditory cortex. Also, individual differences in auditory GABA levels (but not ventrovisual or sensorimotor GABA levels) were associated with individual differences in neural distinctiveness in the auditory cortex in the older adults. These results demonstrate that age-related neural dedifferentiation extends to the auditory cortex and suggest that declining GABA levels may play a role in neural dedifferentiation in older adults., (Copyright © 2019 Elsevier Inc. All rights reserved.)

There is growing evidence that fluctuations in brain activity may exhibit scale-free ("fractal") dynamics. Scale-free signals follow a spectral-power curve of the form P(f ) ∝ f(-β), where spectral power decreases in a power-law fashion with increasing frequency. In this study, we demonstrated that fractal scaling of BOLD fMRI signal is consistently suppressed for different sources of cognitive effort. Decreases in the Hurst exponent (H), which quantifies scale-free signal, was related to three different sources of cognitive effort/task engagement: 1) task difficulty, 2) task novelty, and 3) aging effects. These results were consistently observed across multiple datasets and task paradigms. We also demonstrated that estimates of H are robust across a range of time-window sizes. H was also compared to alternative metrics of BOLD variability (SDBOLD) and global connectivity (Gconn), with effort-related decreases in H producing similar decreases in SDBOLD and Gconn. These results indicate a potential global brain phenomenon that unites research from different fields and indicates that fractal scaling may be a highly sensitive metric for indexing cognitive effort/task engagement.

Background: Fibromyalgia is a chronic widespread pain condition, with patients commonly reporting other symptoms such as sleep difficulties, memory complaints and fatigue. The use of magnetic resonance imaging (MRI) in fibromyalgia has allowed for the detection of neural abnormalities, with alterations in brain activation elicited by experimental pain and alterations in resting state connectivity related to clinical pain., Methods: In this study, we sought to monitor state changes in resting brain connectivity following experimental pressure pain in fibromyalgia patients and healthy controls. Twelve fibromyalgia patients and 15 healthy controls were studied by applying discrete pressure stimuli to the thumbnail bed during MRI. Resting-state functional MRI scanning was performed before and immediately following experimental pressure pain. We investigated changes in functional connectivity to the thalamus and the insular cortex., Results: Acute pressure pain increased insula connectivity to the anterior cingulate and the hippocampus. Additionally, we observed increased thalamic connectivity to the precuneus/posterior cingulate cortex, a known part of the default mode network, in patients but not in controls. This connectivity was correlated with changes in clinical pain., Conclusions: These data reporting changes in resting-state brain activity following a noxious stimulus suggest that the acute painful stimuli may contribute to the alteration of the neural signature of chronic pain. WHAT DOES THIS STUDY/ADD?: In this study acute pain application shows an echo in functional connectivity and clinical pain changes in chronic pain., (© 2016 European Pain Federation - EFIC®)

Longitudinal investigation of the neural correlates of reward processing in depression may represent an important step in defining effective biomarkers for antidepressant treatment outcome prediction, but the reliability of reward-related activation is not well understood. Thirty-seven healthy control participants were scanned using fMRI while performing a reward-related guessing task on two occasions, approximately one week apart. Two main contrasts were examined: right ventral striatum (VS) activation fMRI BOLD signal related to signed prediction errors (PE) and reward expectancy (RE). We also examined bilateral visual cortex activation coupled to outcome anticipation. Significant VS PE-related activity was observed at the first testing session, but at the second testing session, VS PE-related activation was significantly reduced. Conversely, significant VS RE-related activity was observed at time 2 but not time 1. Increases in VS RE-related activity from time 1 to time 2 were significantly associated with decreases in VS PE-related activity from time 1 to time 2 across participants. Intraclass correlations (ICCs) in VS were very low. By contrast, visual cortex activation had much larger ICCs, particularly in individuals with high quality data. Dynamic changes in brain activation are widely predicted, and failure to account for these changes could lead to inaccurate evaluations of the reliability of functional MRI signals. Conventional measures of reliability cannot distinguish between changes specified by algorithmic models of neural function and noisy signal. Here, we provide evidence for the former possibility: reward-related VS activations follow the pattern predicted by temporal difference models of reward learning but have low ICCs.

Stressful life events are related to negative outcomes, including physical and psychological manifestations of distress, and behavioral deficits. Patients diagnosed with breast cancer report impaired attention and working memory prior to adjuvant therapy, which may be induced by distress. In this article, we examine whether brain dynamics show systematic changes due to the distress associated with cancer diagnosis. We hypothesized that impaired working memory is associated with suppression of "long-memory" neuronal dynamics; we tested this by measuring scale-free ("fractal") brain dynamics, quantified by the Hurst exponent (H). Fractal scaling refers to signals that do not occur at a specific time-scale, possessing a spectral power curve P(f)∝ f(-β); they are "long-memory" processes, with significant autocorrelations. In a BOLD functional magnetic resonance imaging study, we scanned three groups during a working memory task: women scheduled to receive chemotherapy or radiotherapy and aged-matched controls. Surprisingly, patients' BOLD signal exhibited greater H with increasing intensity of anticipated treatment. However, an analysis of H and functional connectivity against self-reported measures of psychological distress (Worry, Anxiety, Depression) and physical distress (Fatigue, Sleep problems) revealed significant interactions. The modulation of (Worry, Anxiety) versus (Fatigue, Sleep Problems, Depression) showed the strongest effect, where higher worry and lower fatigue was related to reduced H in regions involved in visuospatial search, attention, and memory processing. This is also linked to decreased functional connectivity in these brain regions. Our results indicate that the distress associated with cancer diagnosis alters BOLD scaling, and H is a sensitive measure of the interaction between psychological versus physical distress., (© 2014 Wiley Periodicals, Inc.)

The aim of this study is to use functional magnetic resonance imaging (fMRI) to prospectively examine pre-treatment predictors of post-treatment fatigue and cognitive dysfunction in women treated with adjuvant chemotherapy for breast cancer. Fatigue and cognitive dysfunction often co-occur in women treated for breast cancer. We hypothesized that pre-treatment factors, unrelated to chemotherapy per se, might increase vulnerability to post-treatment fatigue and cognitive dysfunction. Patients treated with (n = 28) or without chemotherapy (n = 37) and healthy controls (n = 32) were scanned coincident with pre- and one-month post-chemotherapy during a verbal working memory task (VWMT) and assessed for fatigue, worry, and cognitive dysfunction. fMRI activity measures in the frontoparietal executive network were used in multiple linear regression to predict post-treatment fatigue and cognitive function. The chemotherapy group reported greater pre-treatment fatigue than controls and showed compromised neural response, characterized by higher spatial variance in executive network activity, than the non-chemotherapy group. Also, the chemotherapy group reported greater post-treatment fatigue than the other groups. Linear regression indicated that pre-treatment spatial variance in executive network activation predicted post-treatment fatigue severity and cognitive complaints, while treatment group, age, hemoglobin, worry, and mean executive network activity levels did not predict these outcomes. Pre-treatment neural inefficiency (indexed by high spatial variance) in the executive network, which supports attention and working memory, was a better predictor of post-treatment cognitive and fatigue complaints than exposure to chemotherapy per se. This executive network compromise could be a pre-treatment neuromarker of risk, indicating patients most likely to benefit from early intervention for fatigue and cognitive dysfunction.

Mastication is one of the most important orofacial functions. The neurobiological mechanisms of masticatory control have been investigated in animal models, but less so in humans. This project used functional connectivity magnetic resonance imaging (fcMRI) to assess the positive temporal correlations among activated brain areas during a gum-chewing task. Twenty-nine healthy young-adults underwent an fcMRI scanning protocol while they chewed gum. Seed-based fcMRI analyses were performed with the motor cortex and cerebellum as regions of interest. Both left and right motor cortices were reciprocally functionally connected and functionally connected with the post-central gyrus, cerebellum, cingulate cortex, and precuneus. The cerebellar seeds showed functional connections with the contralateral cerebellar hemispheres, bilateral sensorimotor cortices, left superior temporal gyrus, and left cingulate cortex. These results are the first to identify functional central networks engaged during mastication.

It has been shown that varying the spatial versus symbolic nature of stimulus presentation and response production, which affects stimulus-response (S-R) mapping requirements, influences the magnitude of implicit sequence learning (Koch and Hoffman, 2000). Here, we evaluated how spatial and symbolic stimuli and responses affect the neural bases of sequence learning. We selectively eliminated the spatial component of stimulus presentation (spatial vs. symbolic), response execution (manual vs. vocal), or both. Fourteen participants performed the alternating serial reaction time task under these conditions in an MRI scanner, with interleaved acquisition to allow for recording of vocal response reaction times. Nine regions of interest (ROIs) were selected to test the hypothesis that the dorsolateral prefrontal cortex (DLPFC) was preferentially engaged for spatially cued conditions and cerebellum lobule HVI, crus I and II were associated with symbolically cued learning. We found that the left cerebellum lobule HVI was selectively recruited for symbolic learning and the percent signal change in this region was correlated with learning magnitude under the symbolic conditions. In contrast, the DLPFC did not exhibit selective activation for learning under spatial conditions. The inferior parietal lobule exhibited increased activation during learning regardless of the condition, supporting its role in forming an abstract representation of learned sequences. These findings reveal different brain networks that are flexibly engaged depending on the conditions of sequence learning., (Copyright © 2010 Elsevier Inc. All rights reserved.)

This article describes the combination of multivariate Granger causality analysis, temporal down-sampling of fMRI time series, and graph theoretic concepts for investigating causal brain networks and their dynamics. As a demonstration, this approach was applied to analyze epoch-to-epoch changes in a hand-gripping, muscle fatigue experiment. Causal influences between the activated regions were analyzed by applying the directed transfer function (DTF) analysis of multivariate Granger causality with the integrated epoch response as the input, allowing us to account for the effects of several relevant regions simultaneously. Integrated responses were used in lieu of originally sampled time points to remove the effect of the spatially varying hemodynamic response as a confounding factor; using integrated responses did not affect our ability to capture its slowly varying affects of fatigue. We separately modeled the early, middle, and late periods in the fatigue. We adopted graph theoretic concepts of clustering and eccentricity to facilitate the interpretation of the resultant complex networks. Our results reveal the temporal evolution of the network and demonstrate that motor fatigue leads to a disconnection in the related neural network., (2008 Wiley-Liss, Inc.)

This article introduces the measure of integrated local correlation (ILC) for assessing local coherence in the brain using functional magnetic resonance imaging (fMRI) data and characterizes the measure in terms of reproducibility, the effect of physiological noise, and the dependence on image resolution. The coupling of local neuronal processes influences coherence in a voxel's neighborhood. ILC is defined, for each voxel, as the integration of its spatial correlation function. This integrated measure does not require the specification of a neighborhood and, as demonstrated by experimental data, is effectively independent of image resolution. Respiratory and cardiac fluctuations do not considerably alter the ILC value except in isolated areas in and surrounding large vessels. With resting-state fMRI data, ILC was demonstrated to be tissue-specific, higher in gray matter than white matter, and reproducible across consecutive runs in healthy individuals. Within the gray matter, ILC was found to be higher in the default mode network, particularly the posterior and anterior cingulate cortices. Comparing ILC maps obtained from resting state and continuous motor task data, we observed reduced local coherence in the default mode network during the task. Finally, we compared ILC and regional homogeneity by examining their ability to discriminate between gray and white matters in resting state data and found ILC to be more sensitive., ((c) 2007 Wiley-Liss, Inc.)

In this fMRI study, we explore the connectivity among brain regions in a shape-from-motion task using the causal mapping analysis of structural equation modeling (SEM). An important distinction of our approach is that we have adapted SEM from its traditional role in confirmatory analysis to provide utility as an exploratory mapping technique. Our current approaches include (I) detecting brain regions that fit well in a hypothesized neural network model, and (II) identifying the best connectivity model at each brain region. We demonstrate that SEM effectively detects the dorsal and ventral visual pathways from the covariance structure in fMRI data, confirming previous neuroscience results. Further, our SEM mapping methodology found that the two pathways interact through specific cortical areas such as the superior lateral occipital cortex in the perception of shape from motion.

Objective: The mother-child relationship may have important implications for emotional development and adult psychopathology. The objective of this study was to examine brain responses to processing maternal faces in healthy adult women., Methods: Ten healthy adult female volunteers with adequate early-life maternal care and a normal relationship with their living mothers participated in the study. Functional magnetic resonance imaging was used to examine brain responses to pictures of the subject's mother, a close female friend, and 2 age-matched female strangers during passive viewing, valence (emotional), and salience (self-relevance) evaluations., Results: The main contrast of mother, compared with all others (that is, friend and older and younger strangers), demonstrated the following: first, significant activation in the left posterior cingulate cortex-precuneus (PCC-Pcu), collapsed across all tasks; second, right ventromedial prefrontal cortex-anterior cingulate cortex (VMPFC-ACC) activation during the valence condition; and third, left dorsolateral prefrontal cortex (DLPFC) activation during the salience condition. In the region-of-interest analyses, the VMPFC-ACC and DLPFC showed significant activations in response to mothers' faces and deactivation in response to control faces. Among the 3 regions, only VMPFC-ACC activity distinguished the unique processing of one's own mother's face from that of a close friend. PCC-Pcu activations demonstrate a graded response (mother > friend > strangers) and, further, demonstrated differential response with respect to mothering style., Conclusions: The activation in prefrontal and cingulate cortices related to maternal face processing is consistent with their implicated roles in mother-infant interactions, personal familiarity, and emotional and self-relevant processing. These findings suggest a neural basis for maternal attachment and propose a focus for future studies aimed at investigating the impact of disrupted maternal attachment on emotional development.

In this work, recent advances in the field of nonlinear dynamics (NLD) were applied to fMRI data to examine the spatio-temporal properties of BOLD resting state fluctuations. Five human subjects were imaged during resting state (visual fixation) at 3T using single-shot gradient echo planar imaging (EPI). Respiration and cardiac signals were concurrently recorded for retrospectively removing fluctuations due to these physiologic activities. Patterns of singularity in the complex plane (PSC) and Lempel-Ziv complexity (LZ) were used to study the deterministic nonlinearity in resting state fMRI data. The results show that there is greater nonlinearity (higher PSC) and determinism (lower LZ) in gray matter compared to white matter and CSF. In addition, the removal of respiratory and cardiac pulsations decreases the nonlinearity and determinism but does not alter the relative difference between gray matter and white matter. Therefore, our results demonstrate that determinism and nonlinearity in the fMRI data are tissue-specific, suggesting that they reflect native physiologic and metabolic fluctuations and are not a result of physiologic artifacts due to respiration and cardiac pulsation., (Magn Reson Med, 2006. (c) 2006 Wiley-Liss, Inc.)

In this work, we have adapted the directed transfer function (DTF) to fMRI for the analysis of cortical network dynamics. While modern fMRI sequences are capable of sampling at second or sub-second rates, the underlying hemodynamic response limits the true temporal resolution to the order of 6-12 seconds. Therefore, DTF analysis of fMRI is appropriate for characterizing dynamics in brain response which evolves more slowly than the fMRI response, such as those during learning, fatigue and habituation. In such cases, the response to repeated trials will change with time and a summary measure from each trial can be used as input to the DTF analysis because these summary measures are of appropriate sampling rates and are not affected by the sluggishness of the hemodynamic response. As an example, we investigated the dynamic effects of muscle fatigue on the motor network. Specifically, DTF was used as a multivariate measure of the strength and direction of information flow between the various nodes of the network. We found that the primary motor area had a causal influence on the supplementary motor area, pre-motor area and cerebellum, and this influence initially increased with time and diminished towards the end of the experiment, probably as a result of fatigue.

Background: Functional magnetic resonance imaging offers a compelling, new perspective on altered brain function but is sparsely used in studies of anesthetic effect. To examine effects on verbal memory encoding, the authors imaged human brain response to auditory word stimulation using functional magnetic resonance imaging at different concentrations of an agent not previously studied, and tested memory after recovery., Methods: Six male volunteers were studied breathing 0.0, 2.0, and 1.0% end-tidal sevoflurane (awake, deep, and light states, respectively) via laryngeal mask. In each condition, they heard 15 two-syllable English nouns via closed headphones. Each word was repeated 15 times (1/s), followed by 15 s of rest. Blood oxygenation level-dependent brain activations during blocks of stimulation versus rest were assessed with a 3-T Siemens Trio scanner and a 20-voxel spatial extent threshold. Memory was tested approximately 1.5 h after recovery with an auditory recognition task (chance performance = 33% correct)., Results: Scans showed widespread activations (P < 0.005, uncorrected) in the awake state, including bilateral superior temporal, frontal, and parietal cortex, right occipital cortex, bilateral thalamus, striatum, hippocampus, and cerebellum; more limited activations in the light state (bilateral superior temporal gyrus, right thalamus, bilateral parietal cortex, left frontal cortex, and right occipital cortex); and no significant auditory-related activation in the deep state. During recognition testing, subjects correctly selected 77 +/- 12% of words presented while they were awake as "old," versus 32 +/- 15 and 42 +/- 8% (P < 0.01) correct for the light and deep stages, respectively., Conclusions: Sevoflurane induces dose-dependent suppression of auditory blood oxygenation level-dependent signals, which likely limits the ability of words to be processed during anesthesia and compromises memory.

The present fMRI study explores the connectivity among motor areas in a bimanual coordination task using the analysis framework of structural equation modeling (SEM). During bimanual finger tapping at different frequency ratios, temporal correlations of activations between left/right primary motor cortices (MI), left/right PMdc (caudal dorsal premotor area) and supplementary motor cortex (SMA) were detected and used as inputs to the SEM analysis. SEM was extended from its traditional role as a confirmatory analysis to be used as an exploratory technique to determine the most statistically significant connectivity model given a set of cortical areas based on anatomic constraints. The resultant network exhibits coupling from left MI to right MI, links from both PMs to the two MIs, a negative interaction from left PM to right PM, and functional influence from SMA to right MI and right PM, revealing contributions of these areas to bimanual coordination.

Resting state low frequency (<0.08 Hz) fluctuations in MR timecourses that are temporally correlated between functionally related areas have been observed in recent studies. These fluctuations have been assumed to arise from spontaneous blood oxygenation level-dependent (BOLD) oscillations. This work examines the T(2)(*) characteristics of the low frequency fluctuations (functional connectivity) and compares them to those of task activation induced signal changes. Multi-echo spiral data were fit using a mono-exponential decay model to generate T(2)(*) and intensity (I(0)) parameter timecourses. Resultant correlation maps show that both functional connectivity and BOLD activation modulate T(2)(*), not I(0). Regression analysis also finds that both have a linear dependence on echo time. Thus, functional connectivity and task activation MR signal changes appear to arise from the same BOLD-related origins.

Three-dimensional (3D), multi-shot functional magnetic resonance imaging (fMRI) data acquisitions are desirable because of higher resolution and reduced susceptibility artifacts, due to shorter readouts and thinner slices. However, 3D multi-shot techniques are more susceptible to physiological noise, which can increase inter-image variance and lead to inaccurate assessment of activation. This work presents a 3D spiral fMRI data acquisition method at 3 T in which the acquisition of views was ordered to match the phase of either the respiratory or the cardiac cycle. For the acquisition timing parameters used in this work, cardiac ordering was found to reduce inter-image variance by 19%. Cardiac ordered data acquisitions showed the same reduction in variance as sequentially ordered data with cardiac contributions estimated and removed using an externally acquired reference prior to reconstruction. Respiratory ordering showed no reduction in fluctuation noise due to poor alignment of views to the respiratory phase.

Simultaneous multislice acquisition using rosette trajectories (SMART) is a recently introduced functional magnetic resonance imaging pulse sequence that offers high-speed data acquisition by simultaneously exciting several slices. A drawback to its benefit of rapid acquisition is the cumulative effect of the systematic noise present in the off-resonant slices. In this work, a systematic noise compensation method is implemented to gauge the performance of the multislice SMART method versus a single-slice rosette method in a motor activation study. The normalized standard deviation of the noise-compensated image timecourse is reduced by 25% (single-slice rosette) and 62% (SMART), and the normalized volume of motor activation is increased by 25% (single-slice rosette) and 44% (SMART). The noise-compensated SMART method has an average timecourse standard deviation only 9% higher than the noise-compensated single-slice rosette method, while increasing the acquisition rate threefold.

A new acquisition technique for rapid, whole-brain functional MRI is presented. In this technique, several slices are simultaneously acquired using rosette k-space trajectories and a gradient-induced frequency modulation. This modulation together with the spectral properties of the rosette acquisition allow all slices to be reconstructed individually. In functional MRI studies, acquisition rates of 16.7 to 25 images/s were achieved, a threefold improvement over single-slice acquisitions. The raw images showed some increase in noise. However, because this increase is mostly stationary, the functional activation maps showed only a slight increase in noise (8%).

Analysis of the amplitude of low frequency BOLD signal fluctuations (ALFF) in the resting state has recently been used to study the dynamics of intrinsic neural activity. Several studies have also suggested its potential as a biomarker for neuropsychiatric disease. In the current study, we quantified ALFF to determine changes in intrinsic neural oscillations in patients with Parkinson's disease (PD) on and off L-DOPA. Twenty-four PD patients and 24 healthy age-matched controls participated in the study. PD patients underwent two resting state fMRI sessions, either ON a controlled dose of L-DOPA or following a placebo pill (OFF). Control participants underwent one test session. We found that there was increased amplitude of low frequency BOLD signal oscillations for PD patients OFF L-DOPA in the primary and secondary motor areas, and in the middle and medial prefrontal cortices. L-DOPA significantly reduced the amplitude of low frequency oscillations within these regions. The degree of ALFF in the premotor cortex predicted patients' motor performance as measured by the Grooved Pegboard task, such that greater ALFF was associated with poorer performance. These results are in line with the pathophysiology of PD, which shows changes in neural oscillations. Thus, frequency domain analyses of resting state BOLD fMRI signals may provide a useful means to study the pathophysiology of PD and the physiology of the brain's dopaminergic pathways. [ABSTRACT FROM AUTHOR]