Intrinsic Functional Relations Between Human Cerebral Cortex and Thalamus
Washington University, Department of Radiology, Campus Box 8225, 510 South Kingshighway Blvd., St. Louis, MO 63110, USA. Journal of Neurophysiology
(Impact Factor: 2.89).
09/2008; 100(4):1740-8. DOI: 10.1152/jn.90463.2008
The brain is active even in the absence of explicit stimuli or overt responses. This activity is highly correlated within specific networks of the cerebral cortex when assessed with resting-state functional magnetic resonance imaging (fMRI) blood oxygen level-dependent (BOLD) imaging. The role of the thalamus in this intrinsic activity is unknown despite its critical role in the function of the cerebral cortex. Here we mapped correlations in resting-state activity between the human thalamus and the cerebral cortex in adult humans using fMRI BOLD imaging. Based on this functional measure of intrinsic brain activity we partitioned the thalamus into nuclear groups that correspond well with postmortem human histology and connectional anatomy inferred from nonhuman primates. This structure/function correspondence in resting-state activity was strongest between each cerebral hemisphere and its ipsilateral thalamus. However, each hemisphere was also strongly correlated with the contralateral thalamus, a pattern that is not attributable to known thalamocortical monosynaptic connections. These results extend our understanding of the intrinsic network organization of the human brain to the thalamus and highlight the potential of resting-state fMRI BOLD imaging to elucidate thalamocortical relationships.
Available from: Han Zhang
- "Functional connectivity (FC) analysis of resting-state functional magnetic resonance imaging (RS-fMRI) has been suggested as a promising method to study the neural network mechanisms underlying movement disorders, such as Parkinson's disease (PD) [Helmich et al., 2011; Kahan et al., 2014], Huntington's disease [Werner et al., 2014] and ET [Fang et al., 2013; Popa et al., 2013]. Using this method, an FC network similar to the VIM anatomical network composed of the VIM -MC -CBLM circuit has been described in healthy humans in several studies [Anderson et al., 2011; Zhang et al., 2008]. Furthermore, using FC analysis of RSfMRI data, Helmich et al.  have reported that pallidal dysfunction drives the VIM -MC -CBLM circuit to generate tremors in PD, another disease with tremor symptoms. "
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ABSTRACT: The clinical benefits of targeting the ventral intermediate nucleus (VIM) for the treatment of tremors in essential tremor (ET) patients suggest that the VIM is a key hub in the network of tremor generation and propagation and that the VIM can be considered as a seed region to study the tremor network. However, little is known about the central tremor network in ET patients. Twenty-six ET patients and 26 matched healthy controls (HCs) were included in this study. After considering structural and head-motion factors and establishing the accuracy of our seed region, a VIM seed-based functional connectivity (FC) analysis of resting-state functional magnetic resonance imaging (RS-fMRI) data was performed to characterize the VIM FC network in ET patients. We found that ET patients and HCs shared a similar VIM FC network that was generally consistent with the VIM anatomical connectivity network inferred from normal nonhuman primates and healthy humans. Compared with HCs, ET patients displayed VIM-related FC changes, primarily within the VIM-motor cortex (MC)-cerebellum (CBLM) circuit, which included decreased FC in the CBLM and increased FC in the MC. Importantly, tremor severity correlated with these FC changes. These findings provide the first evidence that the pathological tremors observed in ET patients might be based on a physiologically pre-existing VIM - MC - CBLM network and that disruption of FC in this physiological network is associated with ET. Further, these findings demonstrate a potential approach for elucidating the neural network mechanisms underlying this disease. Hum Brain Mapp, 2015. © 2015 Wiley Periodicals, Inc.
Human Brain Mapping 10/2015; DOI:10.1002/hbm.23024 · 5.97 Impact Factor
Available from: Evan Moss Gordon
- "A " consensus " assignment was then derived by collapsing across thresholds (Gordon et al. 2014). We then removed from consideration: (1) small communities that were only present at a single threshold, (2) communities that did not appear to correspond to brain systems described in previous work (Smith et al. 2009; Power et al. 2011; Yeo et al. 2011), and (3) subcortical voxels, which do not tend to robustly sort into systems unless specialized methods are employed (Zhang et al. 2008; Buckner et al. 2011; Greene et al. 2014). "
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ABSTRACT: Recent functional magnetic resonance imaging-based resting-state functional connectivity analyses of group average data have characterized large-scale systems that represent a high level in the organizational hierarchy of the human brain. These systems are likely to vary spatially across individuals, even after anatomical alignment, but the characteristics of this variance are unknown. Here, we characterized large-scale brain systems across two independent datasets of young adults. In these individuals, we were able to identify brain systems that were similar to those described in the group average, and we observed that individuals had consistent topological arrangement of the system features present in the group average. However, the size of system features varied across individuals in systematic ways, such that expansion of one feature of a given system predicted expansion of other parts of the system. Individual-specific systems also contained unique topological features not present in group average systems; some of these features were consistent across a minority of individuals. These effects were observed even after controlling for data quality and for the accuracy of anatomical registration. The variability characterized here has important implications for cognitive neuroscience investigations, which often assume the functional equivalence of aligned brain regions across individuals.
10/2015; Advance access. DOI:10.1093/cercor/bhv239
Available from: Serena Counsell
- "The early establishment of subcortical RSN activity was noted in (Doria et al., 2010) and (Fransson et al., 2009) and, using a seed-based approach, Smyser et al (Smyser et al., 2010) found that connectivity between the thalamus and the motor cortex appeared to be reduced following preterm birth. Toulmin et al. (Toulmin et al., 2015) recently performed a comprehensive examination of thalamocortical connectivity in preterm infants and demonstrated that the functional organisation of the thalamus reveals a concise description of cortical connectivity at term-equivalent age, closely resembling that reported in adults (Zhang et al., 2008). Additionally, specific deficits in thalamic connections to superior frontal and anterior cingulate cortices were observed when compared to term born controls. "
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ABSTRACT: Brain development is adversely affected by preterm birth. Magnetic resonance image analysis has revealed a complex fusion of structural alterations across all tissue compartments that are apparent by term-equivalent age, persistent into adolescence and adulthood, and associated with wide-ranging neurodevelopment disorders. Although functional MRI has revealed the relatively advanced organisational state of the neonatal brain, the full extent and nature of functional disruptions following preterm birth remain unclear. In this study, we apply machine-learning methods to compare whole-brain functional connectivity in preterm infants at term-equivalent age and healthy term-born neonates in order to test the hypothesis that preterm birth results in specific alterations to functional connectivity by term-equivalent age. Functional connectivity networks were estimated in 105 preterm infants and 26 term controls using group independent component analysis and a graphical lasso model. A random-forest based feature selection method was used to identify discriminative edges within each network and a nonlinear support vector machine was used to classify subjects based on functional connectivity alone. We achieved 80% cross-validated classification accuracy informed by a small set of discriminative edges. These edges connected a number of functional nodes in subcortical and cortical grey matter, and most were stronger in term neonates compared to those born preterm. Half of the discriminative edges connected one or more nodes within the basal ganglia. These results demonstrate that functional connectivity in the preterm brain is significantly altered by term-equivalent age, confirming previous reports of altered connectivity between subcortical structures and higher-level association cortex following preterm birth.
Copyright © 2015. Published by Elsevier Inc.
NeuroImage 09/2015; 124(Pt A). DOI:10.1016/j.neuroimage.2015.08.055 · 6.36 Impact Factor
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