Microstructural organization of human insula is linked to its macrofunctional circuitry and predicts cognitive control

Menon, Vinod; Gallardo, Guillermo; Pinsk, Mark A.; Nguyen, Van Dang; Li, Jing-Rebecca; Cai, Weidong; Wassermann, Demián

doi:10.7554/elife.53470

Cited by 60 publications

(33 citation statements)

References 86 publications

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“…The functional and structural correspondence of the insular subregions is imperative for understanding the diverse functions and relations it has with whole-brain networks. There is a wide array of both structural (25,26) and functional (11,27) profiles, providing insight into the connectivity of the distinct regions shown in the present study. The insular subregions are consistent with that in previous functional (28) and meta-analytical ( 23) studies.…”

Section: Discussionmentioning

confidence: 80%

Structural-functional connectivity mapping of the insular cortex: A combined data-driven and meta-analytic topic mapping

Klugah‐Brown¹,

Wang²,

Jiang³

et al. 2021

Preprint

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The insular cortex is an important anatomical integration hub and can serve as a suitable model for exploring structural-functional relationships. In this study, we examined structural and functional magnetic resonance correspondence via the diffusion tensor imaging (DTI) and resting-state functional connectivity (RSFC) profiles of the insular cortex and its mapping with functional networks (FNs) across the brain. We explored these associations primarily by using a data-driven method to independently estimate the structural-functional connectivity in the human insular cortex system. Data were obtained from the Human Connectome Project comprising 108 resting-state functional magnetic resonance neuroimaging (fMRI) and DTI. Brain networks were acquired and defined according to the seven Yeo FNs. In general, we observed moderate to high association between the structural and functional mapping results of three distinct insular subregions: the posterior insula (sensorimotor: RSFC, DTI = 50%, 72%, respectively), dorsal anterior insula (ventral attention: RSFC, DTI = 83%, 83%, respectively), and ventral anterior insula (frontoparietal: RSFC, DTI = 42%, 89%, respectively). We also examined the cognitive and behavioral domains associated with these three insular subregions using meta-analytic topic mapping and found cognitive and behavioral relations to affective processes, reflecting the core properties of the cytoarchitecture. In sum, given the core role of the insula in the human brain, our findings on the correspondence of the insular cortex system between DTI and RSFC mappings provide a novel approach and insight for clinical researchers to detect dysfunctional brain organization in various neurological disorders.

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Section: Discussionmentioning

confidence: 80%

Structural-functional connectivity mapping of the insular cortex: A combined data-driven and meta-analytic topic mapping

Klugah‐Brown¹,

Wang²,

Jiang³

et al. 2021

Preprint

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“…5,22 Additionally, the trajectories were planned tangential to the insular cortex to cover the ventrodorsal functional circuits as well. 4,6,42,43 1) The rostroventral agranular cortex connected to the gyral portion of the anterior cingulate cortex as well as the entorhinal cortex. 2) The intermediate dysganular areas connected to the primary somatosensory cortex, the amygdaloid body, and frontal operculum.…”

Section: Discussionmentioning

confidence: 99%

Frame-based and robot-assisted insular stereo-electroencephalography via an anterior or posterior oblique approach

Machetanz¹,

Grimm²,

Wuttke

et al. 2021

Journal of Neurosurgery

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OBJECTIVE There is an increasing interest in stereo-electroencephalography (SEEG) for invasive evaluation of insular epilepsy. The implantation of insular SEEG electrodes, however, is still challenging due to the anatomical location and complex functional segmentation in both an anteroposterior and ventrodorsal (i.e., superoinferior) direction. While the orthogonal approach (OA) is the shortest trajectory to the insula, it might insufficiently cover these networks. In contrast, the anterior approach (AOA) or posterior oblique approach (POA) has the potential for full insular coverage, with fewer electrodes bearing a risk of being more inaccurate due to the longer trajectory. Here, the authors evaluated the implantation accuracy and the detection of epilepsy-related SEEG activity with AOA and POA insular trajectories. METHODS This retrospective study evaluated the accuracy of 220 SEEG electrodes in 27 patients. Twelve patients underwent a stereotactic frame-based procedure (frame group), and 15 patients underwent a frameless robot-assisted surgery (robot group). In total, 55 insular electrodes were implanted using the AOA or POA considering the insular anteroposterior and ventrodorsal functional organization. The entry point error (EPE) and target point error (TPE) were related to the implantation technique (frame vs robot), the length of the trajectory, and the location of the target (insular vs noninsular). Finally, the spatial distribution of epilepsy-related SEEG activity within the insula is described. RESULTS There were no significant differences in EPE (mean 0.9 ± 0.6 for the nonsinsular electrodes and 1.1 ± 0.7 mm for the insular electrodes) and TPE (1.5 ± 0.8 and 1.6 ± 0.9 mm, respectively), although the length of trajectories differed significantly (34.1 ± 10.9 and 70.1 ± 9.0 mm, repsectively). There was a significantly larger EPE in the frame group than in the robot group (1.5 ± 0.6 vs 0.7 ± 0.5 mm). However, there was no group difference in the TPE (1.5 ± 0.8 vs 1.6 ± 0.8 mm). Epilepsy-related SEEG activity was detected in 42% (23/55) of the insular electrodes. Spatial distribution of this activity showed a clustering in both anteroposterior and ventrodorsal directions. In purely insular onset cases, subsequent insular lesionectomy resulted in a good seizure outcome. CONCLUSIONS The implantation of insular electrodes via the AOA or POA is safe and efficient for SEEG implantation covering both anteroposterior and ventrodorsal functional organization with few electrodes. In this series, there was no decrease in accuracy due to the longer trajectory of insular SEEG electrodes in comparison with noninsular SEEG electrodes. The results of frame-based and robot-assisted implantations were comparable.

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“…Neurobiological markers of frustrative events may thus be characterized by interaction between these 3 subsystems. Evidence from structural and functional connectivity studies suggests that the ventral part of the anterior insula demonstrate close connections with the VS, amygdala and hypothalamus and dmPFC (to a lesser extent), whereas the dorsal part is rather connected with frontal pole, dACC and the aMCC/pre-SMA, which are subserving cognitive control processes (Deen, Pitskel, & Pelphrey, 2011; Ghaziri et al, 2018; Menon et al, 2020; Nomi et al, 2016). Indeed, the IMAGEN Consortium (n=1510) has shown that when rewards were unexpectedly omitted, the ventral striatum was negatively correlated with activity of the insular cortex (bilaterally), the aMCC/pre-SMA and the thalamus (Cao et al, 2019).…”

Section: Discussionmentioning

confidence: 99%

Neural bases of Frustration-Aggression Theory: A multi-domain meta-analysis of functional neuroimaging studies

Dugré

Potvin

2021

Preprint

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Early evidence suggests that unexpected non-reward may increase the risk for aggressive behaviors. Despite the growing interest in understanding brain functions that may be implicated in aggressive behaviors, the neural processes underlying such frustrative events remain largely unknown. Furthermore, meta-analytic results have produced discrepant results, potentially due to substantial differences in the definition of anger/aggression constructs. Therefore, coordinate-based meta-analyses on unexpected non-reward and retaliatory behaviors in healthy subjects were conducted. Conjunction analyses were further examined to discover overlapping brain activations across these meta-analytical maps. Frustrative non-reward deactivated the orbitofrontal cortex, ventral striatum and posterior cingulate cortex, whereas increased activations were observed in midcingulo-insular regions, as well as dorsomedial prefrontal cortex, amygdala, thalamus and periaqueductal gray, when using liberal threshold. Retaliation activated of midcingulo-insular regions, the dorsal caudate and the primary somatosensory cortex. Conjunction analyses revealed that both strongly activated midcingulo-insular regions. Our results underscore the role of anterior midcingulate/pre-supplementary motor area and fronto-insular cortex in both frustration and retaliatory behaviors. A neurobiological framework for understanding frustration-based impulsive aggression is provided.

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Microstructural organization of human insula is linked to its macrofunctional circuitry and predicts cognitive control

Cited by 60 publications

References 86 publications

Structural-functional connectivity mapping of the insular cortex: A combined data-driven and meta-analytic topic mapping

Structural-functional connectivity mapping of the insular cortex: A combined data-driven and meta-analytic topic mapping

Frame-based and robot-assisted insular stereo-electroencephalography via an anterior or posterior oblique approach

Neural bases of Frustration-Aggression Theory: A multi-domain meta-analysis of functional neuroimaging studies

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