A cortical hierarchy of localized and distributed processes revealed via dissociation of task activations, connectivity changes, and intrinsic timescales

AbstractMany studies have identified the role of localized and distributed cognitive functionality by mapping either local task-related activity or distributed functional connectivity (FC). However, few studies have directly explored the relationship between a brain region’s localized task activity and its distributed task FC. Here we systematically evaluated the differential contributions of task-related activity and FC changes to identify a relationship between localized and distributed processes across the cortical hierarchy. We found that across multiple tasks, the magnitude of regional task-evoked activity was high in unimodal areas, but low in transmodal areas. In contrast, we found that task-state FC was significantly reduced in unimodal areas relative to transmodal areas. This revealed a strong negative relationship between localized task activity and distributed FC across cortical regions that was associated with the previously reported principal gradient of macroscale organization. Moreover, this dissociation corresponded to hierarchical cortical differences in the intrinsic timescale estimated from resting-state fMRI and region myelin content estimated from structural MRI. Together, our results contribute to a growing literature illustrating the differential contributions of a hierarchical cortical gradient representing localized and distributed cognitive processes.HighlightsTask activations and functional connectivity changes are negatively correlated across cortexTask activation and connectivity dissociations reflect differences in localized and distributed processes in cortexDifferences in localized and distributed processes are associated with differences in intrinsic timescale organizationDifferences in localized and distributed processes are associated with differences in cortical myelin contentCortical heterogeneity in localized and distributed processes revealed by activity flow mapping prediction error

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Effects of amnesia on processing in the hippocampus and default mode network during a naturalistic memory task: a case study

10.31234/osf.io/e9n8c ◽

2018 ◽

Author(s):

Christiane Oedekoven ◽

James L. Keidel ◽

Stuart Anderson ◽

Angus Nisbet ◽

Chris Bird

Keyword(s):

Functional Connectivity ◽

Episodic Memory ◽

Memory Performance ◽

Memory Task ◽

Structural Mri ◽

Brain Regions ◽

Left Hippocampus ◽

Cortical Regions ◽

The Right ◽

Encoding And Retrieval

Despite their severely impaired episodic memory, individuals with amnesia are able to comprehend ongoing events. Online representations of a current event are thought to be supported by a network of regions centred on the posterior midline cortex (PMC). By contrast, episodic memory is widely believed to be supported by interactions between the hippocampus and these cortical regions. In this MRI study, we investigated the encoding and retrieval of lifelike events (video clips) in a patient with severe amnesia likely resulting from a stroke to the right thalamus, and a group of 20 age-matched controls. Structural MRI revealed grey matter reductions in left hippocampus and left thalamus in comparison to controls. We first characterised the regions activated in the controls while they watched and retrieved the videos. There were no differences in activation between the patient and controls in any of the regions. We then identified a widespread network of brain regions, including the hippocampus, that were functionally connected with the PMC in controls. However, in the patient there was a specific reduction in functional connectivity between the PMC and a region of left hippocampus when both watching and attempting to retrieve the videos. A follow up analysis revealed that in controls the functional connectivity between these regions when watching the videos was correlated with memory performance. Taken together, these findings support the view that the interactions between the PMC and the hippocampus enable the encoding and retrieval of multimodal representations of the contents of an event.

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Impact of anaesthesia on static and dynamic functional connectivity in mice

10.1101/2021.03.18.436098 ◽

2021 ◽

Author(s):

Tomokazu Tsurugizawa ◽

Daisuke Yoshimaru

Keyword(s):

Functional Connectivity ◽

Functional Mri ◽

Resting State ◽

Low Frequency ◽

Resting State Fmri ◽

Brain Network ◽

List Type ◽

Thalamic Nuclei ◽

Dynamic Functional Connectivity ◽

Subcortical Regions

AbstractA few studies have compared the static functional connectivity between awake and anaesthetized states in rodents by resting-state fMRI. However, impact of anaesthesia on static and dynamic fluctuations in functional connectivity has not been fully understood. Here, we developed a resting-state fMRI protocol to perform awake and anaesthetized functional MRI in the same mice. Static functional connectivity showed a widespread decrease under anaesthesia, such as when under isoflurane or a mixture of isoflurane and medetomidine. Several interhemispheric connections were key connections for anaesthetized condition from awake. Dynamic functional connectivity demonstrates the shift from frequent broad connections across the cortex, the hypothalamus, and the auditory-visual cortex to frequent local connections within the cortex only. Fractional amplitude of low frequency fluctuation in the thalamic nuclei decreased under both anaesthesia. These results indicate that typical anaesthetics for functional MRI alters the spatiotemporal profile of the dynamic brain network in subcortical regions, including the thalamic nuclei and limbic system.HighlightsResting-state fMRI was compared between awake and anaesthetized in the same mice.Anaesthesia induced a widespread decrease of static functional connectivity.Anaesthesia strengthened local connections within the cortex.fALFF in the thalamus was decreased by anaesthesia.

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Diffusion property and functional connectivity of superior longitudinal fasciculus underpin human metacognition

10.1101/2020.03.17.994574 ◽

2020 ◽

Author(s):

Yunxuan Zheng ◽

Danni Wang ◽

Qun Ye ◽

Futing Zou ◽

Yao Li ◽

...

Keyword(s):

Functional Connectivity ◽

Structural Integrity ◽

Diffusion Tensor ◽

Memory Task ◽

Resting State Fmri ◽

Precentral Gyrus ◽

Superior Longitudinal Fasciculus ◽

Anterior Portion ◽

Inferior Parietal Cortex ◽

Cortical Regions

AbstractMetacognition as the capacity of monitoring one’s own cognition operates across domains. Here, we addressed whether metacognition in different cognitive domains rely on common or distinct neural substrates with combined diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) techniques. After acquiring DTI and resting-state fMRI data, we asked participants to perform a temporal-order memory task and a perceptual discrimination task, followed by trial-specific confidence judgments. DTI analysis revealed that the structural integrity (indexed by fractional anisotropy) in the anterior portion of right superior longitudinal fasciculus (SLF) was associated with both perceptual and mnemonic metacognitive abilities. Using perturbed mnemonic metacognitive scores produced by inhibiting the precuneus using TMS, the mnemonic metacognition scores did not correlate with individuals’ SLF structural integrity anymore, revealing the relevance of this tract in memory metacognition. In order to further verify the involvement of several cortical regions connected by SLF, we took the TMS-targeted precuneus region as a seed in a functional connectivity analysis and found the functional connectivity between precuneus and two SLF-connected regions (inferior parietal cortex and precentral gyrus) differentially mediated mnemonic but not perceptual metacognition performance. These results illustrate the importance of SLF and a putative white-matter grey-matter circuitry that supports human metacognition.

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Remitted major depression is related to increased functional coupling between ventral striatum and cortical regions in resting state fMRI

European Psychiatry ◽

10.1016/s0924-9338(11)72653-0 ◽

2011 ◽

Vol 26 (S2) ◽

pp. 948-948 ◽

Cited By ~ 1

Author(s):

G. Pail ◽

C. Scharinger ◽

K. Kalcher ◽

W. Huf ◽

R. Boubela ◽

...

Keyword(s):

Functional Connectivity ◽

Orbitofrontal Cortex ◽

Resting State ◽

Ventral Striatum ◽

Resting State Fmri ◽

Anterior Cingulate ◽

Functional Coupling ◽

Healthy Controls ◽

Full Remission ◽

Cortical Regions

IntroductionDysfunction in the basal ganglia has been related to impaired reward processing and anhedonia, a core symptom of Major Depressive Disorder (MDD). In particular, the ventral striatum including the nucleus accumbens is increasingly implicated in the pathophysiology of MDD, but evidence for a specific role during episodes of full remission is lacking so far.ObjectivesTo investigate functional connectivity patterns of resting-state activity in patients in the remitted phase of MDD (rMDD).AimsTo determine whether rMDD is related to disruptions of functional coupling between the ventral striatum and cortical regions.MethodsForty-three remitted depressed patients and thirty-five healthy controls were recruited at Medical University of Vienna, Vienna, Austria, and performed a six minute resting-state fMRI scan. Seed time series were extracted from the preprocessed data using individual masks for ventral striatum and correlated with all nodes in a surface based analysis using FreeSurfer, AFNI and SUMA. The resulting correlation coefficients were then Fishertransformed, group results were determined by comparing group mean smoothed z-scores with a two-sample ttest.ResultsIncreased resting-state functional connectivity was revealed between ventral striatum (seed region) and anterior cingulate cortex as well as orbitofrontal cortex in the rMDD group compared to healthy controls.ConclusionsOur preliminary data is in accordance with the idea that increased functional coupling between the ventral striatum and two major emotion processing regions, the anterior cingulate cortex and the orbitofrontal cortex, may represent a neural mechanism contributing to the maintenance of full remission of MDD.

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Resting state cortico-limbic functional connectivity and dispositional use of emotion regulation strategies: A replication and extension study

10.31219/osf.io/enk2t ◽

2020 ◽

Author(s):

Denise Dörfel ◽

Anne Gärtner ◽

Christoph Scheffel

Keyword(s):

Emotion Regulation ◽

Functional Connectivity ◽

Resting State ◽

Resting State Fmri ◽

Functional Brain Imaging ◽

Distributed Network ◽

Regulation Strategies ◽

Cortical Regions ◽

Network Approaches ◽

Negative Coupling

Neuroimaging functional connectivity analyses have shown that the negative coupling between amygdala and cortical regions is linked to better emotion regulation (ER) in experimental task settings. However, less is known about the neural correlates of ER traits or dispositions. The present study aimed to (1) replicate the findings of differential cortico-limbic coupling during resting state depending on the dispositional use of ER strategies. Furthermore, the study aimed to (2) extend prior findings by examining whether differences in cortico-limbic coupling during resting state predict behavioral and neuronal emotion regulation success in a standard emotion regulation task. To this end, N=107 healthy adults completed the Emotion Regulation Questionnaire (ERQ), underwent an 8-min resting-state fMRI acquisition and completed a reappraisal task during fMRI. Functional connectivity maps of basolateral and centromedial amygdala nuclei were estimated with a seed-based approach regarding associations with regions of the prefrontal cortex, and were then correlated with ERQ scores as well as behavioral and neuronal ER success. All hypotheses and the analysis plan are preregistered at https://osf.io/8wsgu. Opposed to prior findings, we were not able to replicate a correlation of habitual ER strategy use with functional connectivity between amygdala and PFC regions (p > 0.05, FWE-corrected). Furthermore, there was no association of behavioral and neuronal reappraisal success with functional connectivity between amygdala and insula as well as PFC (p > 0.05, FWE-corrected). The present preregistered study calls into question the reported association between individual differences in resting state cortico-limbic connectivity and habitual use of ER strategies. However, ongoing advances in functional brain imaging and distributed network approaches may leverage the identification of reliable functional connectivity patterns that underlie successful emotion regulation.

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A comprehensive macaque fMRI pipeline and hierarchical atlas

10.1101/2020.08.05.237818 ◽

2020 ◽

Author(s):

Benjamin Jung ◽

Paul A. Taylor ◽

Jakob Seidlitz ◽

Caleb Sponheim ◽

Pierce Perkins ◽

...

Keyword(s):

Resting State ◽

Functional Neuroimaging ◽

Spatial Scales ◽

Resting State Fmri ◽

List Type ◽

Processing Efficiency ◽

Population Average ◽

Cortical Hierarchy ◽

Fmri Analysis ◽

Human Primate

AbstractFunctional neuroimaging research in the non-human primate (NHP) has been advancing at a remarkable rate. The increase in available data establishes a need for robust analysis pipelines designed for NHP neuroimaging and accompanying template spaces to standardize the localization of neuroimaging results. Our group recently developed the NIMH Macaque Template (NMT), a high-resolution population average anatomical template and associated neuroimaging resources, providing researchers with a standard space for macaque neuroimaging (Seidlitz, Sponheim et al., 2018). Here, we release NMT v2, which includes both symmetric and asymmetric templates in stereotaxic orientation, with improvements in spatial contrast, processing efficiency, and segmentation. We also introduce the Cortical Hierarchy Atlas of the Rhesus Macaque (CHARM), a hierarchical parcellation of the macaque cerebral cortex with varying degrees of detail. These tools have been integrated into the neuroimaging analysis software AFNI (Cox, 1996) to provide a comprehensive and robust pipeline for fMRI processing, visualization and analysis of NHP data. AFNI’s new @animal_warper program can be used to efficiently align anatomical scans to the NMT v2 space, and afni_proc.py integrates these results with full fMRI processing using macaque-specific parameters: from motion correction through regression modeling. Taken together, the NMT v2 and AFNI represent an all-in-one package for macaque functional neuroimaging analysis, as demonstrated with available demos for both task and resting state fMRI.HighlightsThe NMT v2, a stereotaxically aligned symmetric macaque template, is introduced.A new atlas (CHARM), defined on NMT v2, parcellates the cortex at six spatial scales.AFNI’s @animal_warper aligns and maps data between monkey anatomicals and templates.AFNI’s afni_proc.py facilitates monkey fMRI analysis with automated scripting and QC.Demos of macaque task and resting state fMRI analysis with these tools are provided.

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Brain activity fluctuations propagate as waves traversing the cortical hierarchy

10.1101/2020.08.18.256610 ◽

2020 ◽

Author(s):

Yameng Gu ◽

Lucas E. Sainburg ◽

Sizhe Kuang ◽

Feng Han ◽

Jack W. Williams ◽

...

Keyword(s):

Functional Connectivity ◽

Spontaneous Activity ◽

Resting State ◽

Brain Activity ◽

Resting State Fmri ◽

Hierarchical Organization ◽

Subcortical Structures ◽

Cortical Hierarchy ◽

Neural Origin ◽

The Brain

AbstractThe brain exhibits highly organized patterns of spontaneous activity as measured by resting-state fMRI fluctuations that are being widely used to assess the brain’s functional connectivity. Some evidence suggests that spatiotemporally coherent waves are a core feature of spontaneous activity that shapes functional connectivity, though this has been difficult to establish using fMRI given the temporal constraints of the hemodynamic signal. Here we investigated the structure of spontaneous waves in human fMRI and monkey electrocorticography. In both species, we found clear, repeatable, and directionally constrained activity waves coursed along a spatial axis approximately representing cortical hierarchical organization. These cortical propagations were closely associated with activity changes in distinct subcortical structures, particularly those related to arousal regulation, and modulated across different states of vigilance. The findings demonstrate a neural origin of spatiotemporal fMRI wave propagation at rest and link it to the principal gradient of resting-state fMRI connectivity.

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Brain Activity Fluctuations Propagate as Waves Traversing the Cortical Hierarchy

Cerebral Cortex ◽

10.1093/cercor/bhab064 ◽

2021 ◽

Author(s):

Yameng Gu ◽

Lucas E Sainburg ◽

Sizhe Kuang ◽

Feng Han ◽

Jack W Williams ◽

...

Keyword(s):

Functional Connectivity ◽

Spontaneous Activity ◽

Resting State ◽

Brain Activity ◽

Resting State Fmri ◽

Hierarchical Organization ◽

Subcortical Structures ◽

Cortical Hierarchy ◽

Neural Origin ◽

The Brain

Abstract The brain exhibits highly organized patterns of spontaneous activity as measured by resting-state functional magnetic resonance imaging (fMRI) fluctuations that are being widely used to assess the brain’s functional connectivity. Some evidence suggests that spatiotemporally coherent waves are a core feature of spontaneous activity that shapes functional connectivity, although this has been difficult to establish using fMRI given the temporal constraints of the hemodynamic signal. Here, we investigated the structure of spontaneous waves in human fMRI and monkey electrocorticography. In both species, we found clear, repeatable, and directionally constrained activity waves coursed along a spatial axis approximately representing cortical hierarchical organization. These cortical propagations were closely associated with activity changes in distinct subcortical structures, particularly those related to arousal regulation, and modulated across different states of vigilance. The findings demonstrate a neural origin of spatiotemporal fMRI wave propagation at rest and link it to the principal gradient of resting-state fMRI connectivity.

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Homozygous loss of autism-risk geneCNTNAP2results in reduced local and long-range prefrontal functional connectivity

10.1101/060335 ◽

2016 ◽

Cited By ~ 6

Author(s):

Adam Liska ◽

Alice Bertero ◽

Ryszard Gomolka ◽

Mara Sabbioni ◽

Alberto Galbusera ◽

...

Keyword(s):

Functional Connectivity ◽

Long Range ◽

Brain Connectivity ◽

Resting State Fmri ◽

Autism Spectrum ◽

Loss Of Function ◽

Functional Impairments ◽

Social Investigation ◽

Reduced Frequency ◽

Cortical Regions

AbstractFunctional connectivity aberrancies, as measured with resting-state fMRI (rsfMRI), have been consistently observed in the brain of autism spectrum disorders (ASD) patients. However, the genetic and neurobiological underpinnings of these findings remain unclear. Homozygous mutations in Contactin Associated Protein-like 2 (CNTNAP2), a neurexin-related cell-adhesion protein, are strongly linked to autism and epilepsy. Here we used rsfMRI to show that homozygous mice lackingCntnap2exhibit reduced long-range and local functional connectivity in prefrontal and midline brain “connectivity hubs”. Long-range rsfMRI connectivity impairments affected heteromodal cortical regions and were prominent between fronto-posterior components of the mouse default-mode network (DMN), an effect that was associated with reduced social investigation, a core “autism trait” in mice. Notably, viral tracing revealed reduced frequency of prefrontal-projecting neural clusters in the cingulate cortex ofCntnap2−/−mutants, suggesting a possible contribution of defective mesoscale axonal wiring to the observed functional impairments. Macroscale cortico-cortical white matter organization appeared to be otherwise preserved in these animals. These findings reveal a key contribution of ASD-associated gene CNTNAP2 in modulating macroscale functional connectivity, and suggest that homozygous loss-of-function mutations in this gene may predispose to neurodevelopmental disorders and autism through a selective dysregulation of connectivity in integrative prefrontal areas.

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Assessing uncertainty in connective field estimations from resting state fMRI activity

10.1101/2020.11.02.365452 ◽

2020 ◽

Author(s):

Azzurra Invernizzi ◽

Nicolas Gravel ◽

Koen V. Haak ◽

Remco J. Renken ◽

Frans W. Cornelissen

Keyword(s):

Visual Field ◽

Functional Connectivity ◽

Resting State ◽

Resting State Fmri ◽

Fmri Data ◽

List Type ◽

Spatial Integration ◽

Cortical Areas ◽

Local Functional ◽

Visual Cortical

AbstractConnective Field (CF) modeling estimates the local spatial integration between signals in distinct cortical visual field areas. As we have shown previously using 7T data, CF can reveal the visuotopic organization of visual cortical areas even when applied to BOLD activity recorded in the absence of external stimulation. This indicates that CF modeling can be used to evaluate cortical processing in participants in which the visual input may be compromised. Furthermore, by using Bayesian CF modelling it is possible to estimate the co-variability of the parameter estimates and therefore, apply CF modeling to single cases. However, no previous studies evaluated the (Bayesian) CF model using 3T resting-state fMRI data, although this is important since 3T scanners are much more abundant and more often used in clinical research than 7T ones. In this study, we investigate whether it is possible to obtain meaningful CF estimates from 3T resting state (RS) fMRI data. To do so, we applied the standard and Bayesian CF modeling approaches on two RS scans interleaved by the acquisition of visual stimulation in 12 healthy participants.Our results show that both approaches reveal good agreement between RS- and visual field (VF)-based maps. Moreover, the 3T observations were similar to those previously reported at 7T. In addition, to quantify the uncertainty associated with each estimate in both RS and VF data, we applied our Bayesian CF framework to provide the underlying marginal distribution of the CF parameters. Finally, we show how an additional CF parameter, beta, can be used as a data-driven threshold on the RS data to further improve CF estimates. We conclude that Bayesian CF modeling can characterize local functional connectivity between visual cortical areas from RS data at 3T. In particular, we expect the ability to assess parameter uncertainty in individual participants will be important for future clinical studies.HighlightsLocal functional connectivity between visual cortical areas can be estimated from RS-fMRI data at 3T using both standard CF and Bayesian CF modelling.Bayesian CF modelling quantifies the model uncertainty associated with each CF parameter on RS and VF data, important in particular for future studies on clinical populations.3T observations were qualitatively similar to those previously reported at 7T.

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