Amisulpride and l-DOPA modulate subcortical brain nuclei connectivity in resting-state pharmacologic magnetic resonance imaging.
Ontology highlight
ABSTRACT:
SUBMITTER: Grimm O
PROVIDER: S-EPMC7267910 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:ObjectivesThe new daily persistent headache (NDPH) is a rare primary headache disorder. However, the underlying mechanisms of NDPH remain incompletely understood. This study aims to apply seed-based analysis to explore the functional connectivity (FC) of brainstem nuclei in patients with NDPH using resting-state functional magnetic resonance imaging (MRI).MethodsThe FC analysis from the region of interest (ROI) to whole brain voxels was used to investigate 29 patients with NDPH and 37 well-matched healthy controls (HCs) with 3.0 Tesla MRI. The 76 nuclei in the brainstem atlas were defined as ROIs. Furthermore, we explored the correlations between FC and patients' clinical characteristics and neuropsychological evaluations.ResultsPatients with NDPH exhibited reduced FC in multiple brainstem nuclei compared to HCs (including right inferior medullary reticular formation, right mesencephalic reticular formation, bilateral locus coeruleus, bilateral laterodorsal tegmental nucleus-central gray of the rhombencephalon, median raphe, left medial parabrachial nucleus, periaqueductal gray, and bilateral ventral tegmental area-parabrachial pigmented nucleus complex) and increased FC in periaqueductal gray. No significant correlations were found between the FC of these brain regions and clinical characteristics or neuropsychological evaluations after Bonferroni correction (p > 0.00016).ConclusionsOur results demonstrated that patients with NDPH have abnormal FC of brainstem nuclei involved in the perception and regulation of pain and emotions.
| S-EPMC10958407 | biostudies-literature
Project description:Focal brain lesions can have important remote effects on the function of distant brain regions. The resulting network dysfunction may contribute significantly to behavioral deficits observed after stroke. This study investigates the behavioral significance of changes in the coherence of spontaneous activity in distributed networks after stroke by measuring resting state functional connectivity (FC) using functional magnetic resonance imaging.In acute stroke patients, we measured FC in a dorsal attention network and an arm somatomotor network, and determined the correlation of FC with performance obtained in a separate session on tests of attention and motor function. In particular, we compared the behavioral correlation with intrahemispheric FC to the behavioral correlation with interhemispheric FC.In the attention network, disruption of interhemispheric FC was significantly correlated with abnormal detection of visual stimuli (Pearson r with field effect = -0.624, p = 0.002). In the somatomotor network, disruption of interhemispheric FC was significantly correlated with upper extremity impairment (Pearson r with contralesional Action Research Arm Test = 0.527, p = 0.036). In contrast, intrahemispheric FC within the normal or damaged hemispheres was not correlated with performance in either network. Quantitative lesion analysis demonstrated that our results could not be explained by structural damage alone.These results suggest that lesions cause state changes in the spontaneous functional architecture of the brain, and constrain behavioral output. Clinically, these results validate using FC for assessing the health of brain networks, with implications for prognosis and recovery from stroke, and underscore the importance of interhemispheric interactions.
| S-EPMC2927671 | biostudies-literature
Project description:The periaqueductal gray matter (PAG), a known modulator of somatic pain transmission, shows evidence of interictal functional and structural abnormalities in migraineurs, which may contribute to hyperexcitability along spinal and trigeminal nociceptive pathways, and lead to the migraine attack. The aim of this study was to examine functional connectivity of the PAG in migraine.Using resting-state functional MRI, we compared functional connectivity between PAG and a subset of brain areas involved in nociceptive/somatosensory processing and pain modulation in 17 subjects with migraine, during a pain-free state, versus 17 gender- and age-matched controls. We also assessed the relation between intrinsic resting-state correlations within PAG networks and the average monthly frequency of migraine attacks, as well as allodynia.Our findings show stronger connectivity between the PAG and several brain areas within nociceptive and somatosensory processing pathways in migraineurs versus controls. In addition, as the monthly frequency of migraine attacks worsens, the strength of the connectivity in some areas within these pathways increases, whereas a significant decrease in functional resting-state connectivity between the PAG and brain regions with a predominant role in pain modulation (prefrontal cortex, anterior cingulate, amygdala) can be evidenced. Finally, migraineurs with a history of allodynia exhibit significantly reduced connectivity between PAG, prefrontal regions, and anterior cingulate compared to migraineurs without allodynia.These data reveal interictal dysfunctional dynamics within pain pathways in migraine manifested as an impairment of the descending pain modulatory circuits, likely leading to loss of pain inhibition, and hyperexcitability primarily in nociceptive areas.
| S-EPMC3243965 | biostudies-literature
Project description:Previous studies on brain functional connectivity networks in children have mainly focused on changes in function in specific brain regions, as opposed to whole brain connectivity in healthy children. By analyzing the independent components of activation and network connectivity between brain regions, we examined brain activity status and development trends in children aged 3 and 5 years. These data could provide a reference for brain function rehabilitation in children with illness or abnormal function. We acquired functional magnetic resonance images from 15 3-year-old children and 15 5-year-old children under natural sleep conditions. The participants were recruited from five kindergartens in the Nanshan District of Shenzhen City, China. The parents of the participants signed an informed consent form with the premise that they had been fully informed regarding the experimental protocol. We used masked independent component analysis and BrainNet Viewer software to explore the independent components of the brain and correlation connections between brain regions. We identified seven independent components in the two groups of children, including the executive control network, the dorsal attention network, the default mode network, the left frontoparietal network, the right frontoparietal network, the salience network, and the motor network. In the default mode network, the posterior cingulate cortex, medial frontal gyrus, and inferior parietal lobule were activated in both 3- and 5-year-old children, supporting the "three-brain region theory" of the default mode network. In the frontoparietal network, the frontal and parietal gyri were activated in the two groups of children, and functional connectivity was strengthened in 5-year-olds compared with 3-year-olds, although the nodes and network connections were not yet mature. The high-correlation network connections in the default mode networks and dorsal attention networks had been significantly strengthened in 5-year-olds vs. 3-year-olds. Further, the salience network in the 3-year-old children included an activated insula/inferior frontal gyrus-anterior cingulate cortex network circuit and an activated thalamus-parahippocampal-posterior cingulate cortex-subcortical regions network circuit. By the age of 5 years, nodes and high-correlation network connections (edges) were reduced in the salience network. Overall, activation of the dorsal attention network, default mode network, left frontoparietal network, and right frontoparietal network increased (the volume of activation increased, the signals strengthened, and the high-correlation connections increased and strengthened) in 5-year-olds compared with 3-year-olds, but activation in some brain nodes weakened or disappeared in the salience network, and the network connections (edges) were reduced. Between the ages of 3 and 5 years, we observed a tendency for function in some brain regions to be strengthened and for the generalization of activation to be reduced, indicating that specialization begins to develop at this time. The study protocol was approved by the local ethics committee of the Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences in China with approval No. SIAT-IRB-131115-H0075 on November 15, 2013.
| S-EPMC6524509 | biostudies-literature
Project description:Neuroimaging studies typically consider white matter as unchanging in different neural and metabolic states. However, a recent study demonstrated that white matter signal regression (WMSR) produced a similar loss of neurometabolic information to global (whole-brain) signal regression (GSR) in resting-state functional magnetic resonance imaging (R-fMRI) data. This was unexpected as the loss of information would normally be attributed to neural activity within gray matter correlating with the global R-fMRI signal. Indeed, WMSR has been suggested as an alternative to avoid such pitfalls in GSR. To address these concerns about tissue-specific regression in R-fMRI data analysis, we performed GSR, WMSR, and gray matter signal regression (GMSR) on R-fMRI data from the 1000 Functional Connectomes Project. We describe several regional and motion-related differences between different types of regressions. However, the overall effects of concern, particularly network-specific alteration of correlation coefficients, are present for all regressions. This suggests that tissue-specific regression is not an adequate strategy to counter pitfalls of GSR. Conversely, if GSR is desired, but the studied disease state excludes either gray matter or white matter from analysis (e.g., due to tissue atrophy), our results indicate that WMSR or GMSR may reproduce the gross effects of GSR.
| S-EPMC5653143 | biostudies-literature
Project description:Schizophrenia and bipolar disorder share overlapping symptoms and risk genes. Shared aberrant functional connectivity is hypothesized in both disorders and in relatives.We investigated resting state functional magnetic resonance imaging in 70 schizophrenia and 64 psychotic bipolar probands, their respective first-degree relatives (n = 70 and 52), and 118 healthy subjects. We used independent component analysis to identify components representing various resting state networks and assessed spatial aspects of functional connectivity within all networks. We first investigated group differences using five-level, one-way analysis of covariance (ANCOVA), followed by post hoc t tests within regions displaying ANCOVA group differences and correlation of such functional connectivity measures with symptom ratings to examine clinical relationships.Seven networks revealed abnormalities (five-level one-way ANCOVA, family-wise error correction p < .05): A) fronto-occipital, B) midbrain/cerebellum, C) frontal/thalamic/basal ganglia, D) meso/paralimbic, E) posterior default mode network, F) fronto-temporal/paralimbic and G) sensorimotor networks. Abnormalities in networks B and F were unique to schizophrenia probands. Furthermore, abnormalities in networks D and E were common to both patient groups. Finally, networks A, C, and G showed abnormalities shared by probands and their relative groups. Negative correlation with Positive and Negative Syndrome Scale negative and positive scores were found in regions within network C and F respectively, and positive correlation with Positive and Negative Syndrome Scale negative scores was found in regions in network D among schizophrenia probands only.Schizophrenia, psychotic bipolar probands, and their relatives share both unique and overlapping within-network brain connectivity abnormalities, revealing potential psychosis endophenotypes.
| S-EPMC3752322 | biostudies-other
Project description:Blood-level oxygenation-dependent (BOLD) functional magnetic resonance imaging (fMRI) is the most common modality to study functional connectivity in the human brain. Most research to date has focused on connectivity between pairs of brain regions. However, attention has recently turned towards connectivity involving more than two regions, that is, higher-order connectivity. It is not yet clear how higher-order connectivity can best be quantified. The measures that are currently in use cannot distinguish between pairwise (i.e., second-order) and higher-order connectivity. We show that genuine higher-order connectivity can be quantified by using multivariate cumulants. We explore the use of multivariate cumulants for quantifying higher-order connectivity and the performance of block bootstrapping for statistical inference. In particular, we formulate a generative model for fMRI signals exhibiting higher-order connectivity and use it to assess bias, standard errors, and detection probabilities. Application to resting-state fMRI data from the Human Connectome Project demonstrates that spontaneous fMRI signals are organized into higher-order networks that are distinct from second-order resting-state networks. Application to a clinical cohort of patients with multiple sclerosis further demonstrates that cumulants can be used to classify disease groups and explain behavioral variability. Hence, we present a novel framework to reliably estimate genuine higher-order connectivity in fMRI data which can be used for constructing hyperedges, and finally, which can readily be applied to fMRI data from populations with neuropsychiatric disease or cognitive neuroscientific experiments.
| S-EPMC10960559 | biostudies-literature
Project description:Introduction: The selection of an appropriate window size, window function, and functional connectivity (FC) metric in the sliding window method is not straightforward due to the absence of ground truth. Methods: A previously proposed wavelet-based method was accordingly adjusted for estimating time-varying FC (TVFC) and was applied to a large high-quality, low-motion dataset of 400 resting-state functional magnetic resonance imaging data. Specifically, the wavelet coherence magnitude and relative phase were averaged across wavelet (frequency) scales to yield TVFC and synchronization patterns. To assess whether the observed fluctuations in TVFC were statistically significant (dynamic FC [dFC]; the distinction between TVFC and dFC is intentional), surrogate data were generated using the multivariate phase randomization (MVPR) and multivariate autoregressive randomization (MVAR) methods to define the null hypothesis of dFC absence. Results: By averaging across all frequencies, core regions of the default mode network (DMN; medial prefrontal and posterior cingulate cortices, inferior parietal lobes, hippocampal formation) were found to exhibit dFC (test-retest reproducibility of 90%) and were also synchronized in activity (-15° ≤ phase ≤15°). When averaging across distinct frequency bands, the same dynamic connections were identified, with the majority of them identified in the frequency range (0.01, 0.198) Hz, though with lower test-retest reproducibility (<66%). Additional analysis suggested that MVPR method better preserved properties (p < 10-10), including time-averaged coherence, of the original data compared with MVAR approach. Conclusions: The wavelet-based approach identified dynamic associations between the core DMN regions with fewer choices in parameters, compared with sliding window method. Impact statement We employed a wavelet-based method, previously used in the literature, and proposed modifications to assess time-varying functional connectivity in resting-state functional magnetic resonance imaging. With this approach, dynamic connections within the default mode network were identified, involving the medial prefrontal and posterior cingulate cortices, inferior parietal lobes, and hippocampal formation, which were also highly consistent in test-retest analysis (test-retest reproducibility of 90%), without the need to select window size, window function, and functional connectivity metric as with the sliding window method, whereby no consensus on the appropriate choices of hyperparameters currently exists in the literature.
| S-EPMC9271336 | biostudies-literature
Project description:The authors investigated the changes in connectivity networks of the bilateral primary motor cortex (M1) of subcortical stroke patients using a multimodal neuroimaging approach with antiplatelet therapy. Nineteen patients were scanned at 2 time points: before and 1 month after the treatment. The authors assessed the resting-state functional connectivity (FC) and probabilistic fiber tracking of left and right M1 of every patient, and then compared these results to the 15 healthy controls. The authors also evaluated the correlations between the neuroimaging results and clinical scores.Compared with the controls, the patients showed a significant decrease of FC in the contralateral motor cortex before treatment, and the disrupted FC was restored after treatment. The fiber tracking results in the controls indicated that the body of the corpus callosum should be the main pathway connecting the M1 and contralateral hemispheres. All patients exhibited reduced probability of structural connectivity within this pathway before treatment and which was restored after treatment. Significant correlations were also found in these patients between the connectivity results and clinical scores, which might imply that the connectivity of M1 can be used to evaluate the motor skills in stroke patients.These findings can help elucidate the neural mechanisms responsible for the brain connectivity recovery after stroke.
| S-EPMC4753872 | biostudies-other
Project description:Studies have revealed abnormalities in resting-state functional connectivity in those with major depressive disorder specifically in areas such as the dorsal anterior cingulate, thalamus, amygdala, the pallidostriatum and subgenual cingulate. However, the effect of antidepressant medications on human brain function is less clear and the effect of these drugs on resting-state functional connectivity is unknown. Forty volunteers matched for age and gender with no previous psychiatric history received either citalopram (SSRI; selective serotonergic reuptake inhibitor), reboxetine (SNRI; selective noradrenergic reuptake inhibitor) or placebo for 7 days in a double-blind design. Using resting-state functional magnetic resonance imaging and seed based connectivity analysis we selected the right nucleus accumbens, the right amygdala, the subgenual cingulate and the dorsal medial prefrontal cortex as seed regions. Mood and subjective experience were also measured before and after drug administration using self-report scales. Despite no differences in mood across the three groups, we found reduced connectivity between the amygdala and the ventral medial prefrontal cortex in the citalopram group and the amygdala and the orbitofrontal cortex for the reboxetine group. We also found reduced striatal-orbitofrontal cortex connectivity in the reboxetine group. These data suggest that antidepressant medications can decrease resting-state functional connectivity independent of mood change and in areas known to mediate reward and emotional processing in the brain. We conclude that hypothesis-driven seed based analysis of resting-state fMRI supports the proposition that antidepressant medications might work by normalising the elevated resting-state functional connectivity seen in depressed patients.
| S-EPMC3141109 | biostudies-literature