Striatal functional connectivity networks are modulated by fMRI resting state conditions

Gopinath, Kaundinya; Ringe, Wendy K; Goyal, Arun; Carter, Kirstine; Dinse, Hubert R.; Haley, Robert W.; Briggs, Richard W.

doi:10.1016/j.neuroimage.2010.07.021

Cited by 26 publications

(18 citation statements)

References 76 publications

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“…The VS showed negative connectivity with the visual cortices, posterior parietal cortex, temporoparietal junction, superior temporal gyri, precentral cortex, lateral frontal cortices including the dorsolateral prefrontal cortex, inferior frontal cortices, posterior thalamus/pulvinar, parahippocampal gyrus, and the cerebellum (Figure 3). These results are consistent with previous findings of resting state VS connectivity with the medial orbitofrontal cortex and ventral caudate (Baliki et al, 2013; Cauda et al, 2011; Di Martino et al, 2008; Gopinath et al, 2011), amygdala and midbrain (Cauda et al, 2011), and hippocampus (Cauda et al, 2011; Kahn and Shohamy, 2013). …”

Section: Resultssupporting

confidence: 93%

Resting state functional connectivity of the basal nucleus of Meynert in humans: In comparison to the ventral striatum and the effects of age

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Zhang

et al. 2014

NeuroImage

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The basal nucleus of Meynert (BNM) provides the primary cholinergic inputs to the cerebral cortex. Loss of neurons in the BNM is linked to cognitive deficits in Alzheimer’s disease and other degenerative conditions. Numerous animal studies described cholinergic and non-cholinergic neuronal responses in the BNM; however, work in humans has been hampered by the difficulty of defining the BNM anatomically. Here, on the basis of a previous study that delineated the BNM of post-mortem human brains in a standard stereotaxic space, we sought to examine functional connectivity of the BNM, as compared to the nucleus accumbens (or ventral striatum, VS), in a large resting state functional magnetic resonance imaging data set. The BNM and VS shared but also showed a distinct pattern of cortical and subcortical connectivity. Compared to the VS, the BNM showed stronger positive connectivity with the putamen, pallidum, thalamus, amygdala and midbrain, as well as the anterior cingulate cortex, supplementary motor area and pre-supplementary motor area, a network of brain regions that respond to salient stimuli and orchestrate motor behavior. In contrast, compared to the BNM, the VS showed stronger positive connectivity with the ventral caudate and medial orbitofrontal cortex, areas implicated in reward processing and motivated behavior. Furthermore, the BNM and VS each showed extensive negative connectivity with visual and lateral prefrontal cortices. Together, the distinct cerebral functional connectivities support the role of the BNM in arousal, saliency responses and cognitive motor control and the VS in reward related behavior. Considering the importance of BNM in age-related cognitive decline, we explored the effects of age on BNM and VS connectivities. BNM connectivity to the visual and somatomotor cortices decreases while connectivity to subcortical structures including the midbrain, thalamus, and pallidum increases with age. These findings of age-related changes of cerebral functional connectivity of the BNM may facilitate research of the neural bases of cognitive decline in health and illness.

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Section: Resultssupporting

confidence: 93%

Resting state functional connectivity of the basal nucleus of Meynert in humans: In comparison to the ventral striatum and the effects of age

Ide

Zhang

et al. 2014

NeuroImage

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“…A small sensorimotor area was also significantly positively correlated with the VST, but the connectivity was weaker than the other areas. This was supported by previous classic studies that demonstrated that the VST works as a functional interface between emotion regulation and sensorimotor control (Haber et al, 1995;Gopinath et al, 2011). The results for the left and right VST are shown in Fig.…”

Section: The Rs-fc Patterns Of the Vstsupporting

confidence: 85%

Epistatic interaction of BDNF and COMT on the frontostriatal system

et al. 2015

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“…Participants were instructed to keep their eyes open and blink at a normal rate during the resting-state scans (Gopinath et al, 2011). rsFMRI scans were acquired with a multiband slice-accelerated gradient-echo EPI sequence (Moeller et al, 2010) with imaging parameters as follows: field of view (FOV) = 220 mm; repetition time (TR)/echo time (TE) = 2000 / 24 msec; flip angle (FA) = 45°; phase partial Fourier factor = 5/8; 48 interleaved 3 · 3 mm resolution axial slices of 3 mm width covering the whole brain; and 270 scan volumes.…”

Section: Image Acquisitionmentioning

confidence: 99%

“…3) exhibited anticorrelations with the ventral striatum, amygdala, and hippocampus head-all components of the emotion and limbic networks. Thus, some of the anticorrelations in the rsFC network architecture may also reflect reciprocal modulations between sensorimotor and emotion networks (Drevets and Raichle, 1998;Gopinath et al, 2011).…”

Section: Hacs and Mechanisms Subserving Associated Anticorrelation Mapsmentioning

confidence: 99%

Hubs of Anticorrelation in High-Resolution Resting-State Functional Connectivity Network Architecture

et al. 2015

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A major focus of brain research recently has been to map the resting-state functional connectivity (rsFC) network architecture of the normal brain and pathology through functional magnetic resonance imaging. However, the phenomenon of anticorrelations in resting-state signals between different brain regions has not been adequately examined. The preponderance of studies on resting-state fMRI (rsFMRI) have either ignored anticorrelations in rsFC networks or adopted methods in data analysis, which have rendered anticorrelations in rsFC networks uninterpretable. The few studies that have examined anticorrelations in rsFC networks using conventional methods have found anticorrelations to be weak in strength and not very reproducible across subjects. Anticorrelations in rsFC network architecture could reflect mechanisms that subserve a number of important brain processes. In this preliminary study, we examined the properties of anticorrelated rsFC networks by systematically focusing on negative cross-correlation coefficients (CCs) among rsFMRI voxel time series across the brain with graph theory-based network analysis. A number of methods were implemented to enhance the neuronal specificity of resting-state functional connections that yield negative CCs, although at the cost of decreased sensitivity. Hubs of anticorrelation were seen in a number of cortical and subcortical brain regions. Examination of the anticorrelation maps of these hubs indicated that negative CCs in rsFC network architecture highlight a number of regulatory interactions between brain networks and regions, including reciprocal modulations, suppression, inhibition, and neurofeedback.

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Striatal functional connectivity networks are modulated by fMRI resting state conditions

Cited by 26 publications

References 76 publications

Resting state functional connectivity of the basal nucleus of Meynert in humans: In comparison to the ventral striatum and the effects of age

Resting state functional connectivity of the basal nucleus of Meynert in humans: In comparison to the ventral striatum and the effects of age

Epistatic interaction of BDNF and COMT on the frontostriatal system

Hubs of Anticorrelation in High-Resolution Resting-State Functional Connectivity Network Architecture

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