Altered fMRI resting-state connectivity in individuals with fibromyalgia on acute pain stimulation.

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.

The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism.

Autism spectrum disorders (ASDs) represent a formidable challenge for psychiatry and neuroscience because of their high prevalence, lifelong nature, complexity and substantial heterogeneity. Facing these obstacles requires large-scale multidisciplinary efforts. Although the field of genetics has pioneered data sharing for these reasons, neuroimaging had not kept pace. In response, we introduce the Autism Brain Imaging Data Exchange (ABIDE)-a grassroots consortium aggregating and openly sharing 1112 existing resting-state functional magnetic resonance imaging (R-fMRI) data sets with corresponding structural MRI and phenotypic information from 539 individuals with ASDs and 573 age-matched typical controls (TCs; 7-64 years) (http://fcon_1000.projects.nitrc.org/indi/abide/). Here, we present this resource and demonstrate its suitability for advancing knowledge of ASD neurobiology based on analyses of 360 male subjects with ASDs and 403 male age-matched TCs. We focused on whole-brain intrinsic functional connectivity and also survey a range of voxel-wise measures of intrinsic functional brain architecture. Whole-brain analyses reconciled seemingly disparate themes of both hypo- and hyperconnectivity in the ASD literature; both were detected, although hypoconnectivity dominated, particularly for corticocortical and interhemispheric functional connectivity. Exploratory analyses using an array of regional metrics of intrinsic brain function converged on common loci of dysfunction in ASDs (mid- and posterior insula and posterior cingulate cortex), and highlighted less commonly explored regions such as the thalamus. The survey of the ABIDE R-fMRI data sets provides unprecedented demonstrations of both replication and novel discovery. By pooling multiple international data sets, ABIDE is expected to accelerate the pace of discovery setting the stage for the next generation of ASD studies.

L-DOPA changes spontaneous low-frequency BOLD signal oscillations in Parkinson's disease: a resting state fMRI study.

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.

Age differences in symbolic representations of motor sequence learning.

We recently reported that young adults (YA) preferentially recruit cerebellar lobule HVI for symbolic motor sequence learning [3]. Learning magnitude in the symbolic condition was correlated with activation level in lobule HVI. Here, we evaluated age differences in the symbolic representation of motor sequence learning. Fourteen YA and 14 older adults (OA) performed the alternating serial reaction time task (ASRT) under conditions in which the spatial processing component was selectively eliminated from stimulus presentation (spatial versus symbolic), response execution (manual versus vocal), or both. Results showed that OA had reduced learning magnitudes relative to YA. Using the cerebellum lobule HVI as a region-of-interest, we found that OA had significantly lower activation in this region than YA during the symbolic learning conditions (FWE, P<0.05). Similar to YA, OA also showed a significant correlation between learning magnitude and cerebellar activation in the symbolic conditions. These results suggest that although YA and OA recruit similar neural networks during implicit learning, OA under-recruit relevant brain areas which may partially explain their implicit sequence learning deficits.

Symbolic representations in motor sequence learning.

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.

T(2)(*) dependence of low frequency functional connectivity.

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.

Systematic noise compensation for simultaneous multislice acquisition using rosette trajectories (SMART).

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.

Simultaneous multislice acquisition using rosette trajectories (SMART): a new imaging method for functional MRI.

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%).