scholarly journals Human subsystems of medial temporal lobes extend locally to amygdala nuclei and globally to an allostatic-interoceptive system

2019 ◽  
Author(s):  
Adriana L. Ruiz-Rizzo ◽  
Florian Beissner ◽  
Kathrin Finke ◽  
Hermann J. Müller ◽  
Claus Zimmer ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Large Scale ◽  
Local Level ◽  
Resting State Fmri ◽  
Medial Temporal Lobes ◽  
Default Mode ◽  
Temporal Lobes ◽  
Dual Regression ◽  
Slow Activity ◽  
Global Brain

AbstractIn mammals, the hippocampus, entorhinal, perirhinal, and parahippocampal cortices (i.e., core regions of the human medial temporal lobes, MTL) are locally interlaced with the adjacent amygdala nuclei at the structural and functional levels. At the global brain level, the human MTL has been described as part of the default mode network whereas amygdala nuclei as parts of the salience network, with both networks forming collectively a large-scale brain system supporting allostatic-interoceptive functions. We hypothesized (i) that intrinsic functional connectivity of slow activity fluctuations would reveal human MTL subsystems locally extending to the amygdala; and (ii) that these extended local subsystems would be globally embedded in large-scale brain systems supporting allostatic-interoceptive functions. From the resting-state fMRI data of three independent samples of cognitively healthy adults (one main and two replication samples: Ns = 101, 61, and 29, respectively), we analyzed the functional connectivity of fluctuating ongoing BOLD-activity within and outside the amygdala-MTL in a data-driven way using masked independent component and dual-regression analyses. We found that at the local level MTL subsystems extend to the amygdala and are functionally organized along the longitudinal amygdala-MTL axis. These subsystems were characterized by a consistent involvement of amygdala, hippocampus, and entorhinal cortex, but a variable participation of perirhinal and parahippocampal regions. At the global level, amygdala-MTL subsystems selectively connected to salience, thalamic-brainstem, and default mode networks – the major cortical and subcortical parts of the allostatic-interoceptive system. These results provide evidence for integrated amygdala-MTL subsystems in humans, which are embedded within a larger allostatic-interoceptive system.

scholarly journals Within- and across-network alterations of the sensorimotor network in Parkinson’s disease

2021 ◽  
Author(s):  
Julian Caspers ◽  
Christian Rubbert ◽  
Simon B. Eickhoff ◽  
Felix Hoffstaedter ◽  
Martin Südmeyer ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Functional Connectivity ◽  
Large Scale ◽  
Resting State Fmri ◽  
Systematic Evaluation ◽  
Sensorimotor Network ◽  
Dual Regression ◽  
Group Ica

Abstract Purpose Parkinson’s disease (PD) is primarily defined by motor symptoms and is associated with alterations of sensorimotor areas. Evidence for network changes of the sensorimotor network (SMN) in PD is inconsistent and a systematic evaluation of SMN in PD yet missing. We investigate functional connectivity changes of the SMN in PD, both, within the network, and to other large-scale connectivity networks. Methods Resting-state fMRI was assessed in 38 PD patients under long-term dopaminergic treatment and 43 matched healthy controls (HC). Independent component analysis (ICA) into 20 components was conducted and the SMN was identified within the resulting networks. Functional connectivity within the SMN was analyzed using a dual regression approach. Connectivity between the SMN and the other networks from group ICA was investigated with FSLNets. We investigated for functional connectivity changes between patients and controls as well as between medication states (OFF vs. ON) in PD and for correlations with clinical parameters. Results There was decreased functional connectivity within the SMN in left inferior parietal and primary somatosensory cortex in PD OFF. Across networks, connectivity between SMN and two motor networks as well as two visual networks was diminished in PD OFF. All connectivity decreases partially normalized in PD ON. Conclusion PD is accompanied by functional connectivity losses of the SMN, both, within the network and in interaction to other networks. The connectivity changes in short- and long-range connections are probably related to impaired sensory integration for motor function in PD. SMN decoupling can be partially compensated by dopaminergic therapy.

Structural Changes in Thalamic Nuclei Across Prodromal and Clinical Alzheimer’s Disease

2021 ◽  
pp. 1-11
Author(s):  
Adam S. Bernstein ◽  
Steven Z. Rapcsak ◽  
Michael Hornberger ◽  
Manojkumar Saranathan ◽  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Large Scale ◽  
Structural Changes ◽  
Thalamic Nuclei ◽  
Medial Temporal Lobes ◽  
Cognitive Changes ◽  
Temporal Lobes ◽  
Medial Geniculate ◽  
Healthy Control

Background: Increasing evidence suggests that thalamic nuclei may atrophy in Alzheimer’s disease (AD). We hypothesized that there will be significant atrophy of limbic thalamic nuclei associated with declining memory and cognition across the AD continuum. Objective: The objective of this work was to characterize volume differences in thalamic nuclei in subjects with early and late mild cognitive impairment (MCI) as well as AD when compared to healthy control (HC) subjects using a novel MRI-based thalamic segmentation technique (THOMAS). Methods: MPRAGE data from the ADNI database were used in this study (n = 540). Healthy control (n = 125), early MCI (n = 212), late MCI (n = 114), and AD subjects (n = 89) were selected, and their MRI data were parcellated to determine the volumes of 11 thalamic nuclei for each subject. Volumes across the different clinical subgroups were compared using ANCOVA. Results: There were significant differences in thalamic nuclei volumes between HC, late MCI, and AD subjects. The anteroventral, mediodorsal, pulvinar, medial geniculate, and centromedian nuclei were significantly smaller in subjects with late MCI and AD when compared to HC subjects. Furthermore, the mediodorsal, pulvinar, and medial geniculate nuclei were significantly smaller in early MCI when compared to HC subjects. Conclusion: This work highlights nucleus specific atrophy within the thalamus in subjects with early and late MCI and AD. This is consistent with the hypothesis that memory and cognitive changes in AD are mediated by damage to a large-scale integrated neural network that extends beyond the medial temporal lobes.

Attentional Fluctuations Influence the Neural Fidelity and Connectivity of Stimulus Representations

2018 ◽  
Vol 30 (9) ◽  
pp. 1209-1228 ◽  
Author(s):  
David Rothlein ◽  
Joseph DeGutis ◽  
Michael Esterman
Keyword(s):  
Functional Connectivity ◽  
Large Scale ◽  
Brain Networks ◽  
Relevant Information ◽  
Mental States ◽  
Attention Task ◽  
Default Mode ◽  
Neural Representations ◽  
Similarity Structure ◽  
Similarity Matrices

Attention is thought to facilitate both the representation of task-relevant features and the communication of these representations across large-scale brain networks. However, attention is not “all or none,” but rather it fluctuates between stable/accurate (in-the-zone) and variable/error-prone (out-of-the-zone) states. Here we ask how different attentional states relate to the neural processing and transmission of task-relevant information. Specifically, during in-the-zone periods: (1) Do neural representations of task stimuli have greater fidelity? (2) Is there increased communication of this stimulus information across large-scale brain networks? Finally, (3) can the influence of performance-contingent reward be differentiated from zone-based fluctuations? To address these questions, we used fMRI and representational similarity analysis during a visual sustained attention task (the gradCPT). Participants ( n = 16) viewed a series of city or mountain scenes, responding to cities (90% of trials) and withholding to mountains (10%). Representational similarity matrices, reflecting the similarity structure of the city exemplars ( n = 10), were computed from visual, attentional, and default mode networks. Representational fidelity (RF) and representational connectivity (RC) were quantified as the interparticipant reliability of representational similarity matrices within (RF) and across (RC) brain networks. We found that being in the zone was characterized by increased RF in visual networks and increasing RC between visual and attentional networks. Conversely, reward only increased the RC between the attentional and default mode networks. These results diverge with analogous analyses using functional connectivity, suggesting that RC and functional connectivity in tandem better characterize how different mental states modulate the flow of information throughout the brain.

scholarly journals Organization of Propagated Intrinsic Brain Activity in Individual Humans

2019 ◽  
Vol 30 (3) ◽  
pp. 1716-1734 ◽  
Author(s):  
Ryan V Raut ◽  
Anish Mitra ◽  
Scott Marek ◽  
Mario Ortega ◽  
Abraham Z Snyder ◽  
...  
Keyword(s):  
Resting State ◽  
Large Scale ◽  
Cortical Excitability ◽  
Brain Activity ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Brain Organization ◽  
Individual Level ◽  
Slow Activity ◽  
Lag Structure

Abstract Spontaneous infra-slow (<0.1 Hz) fluctuations in functional magnetic resonance imaging (fMRI) signals are temporally correlated within large-scale functional brain networks, motivating their use for mapping systems-level brain organization. However, recent electrophysiological and hemodynamic evidence suggest state-dependent propagation of infra-slow fluctuations, implying a functional role for ongoing infra-slow activity. Crucially, the study of infra-slow temporal lag structure has thus far been limited to large groups, as analyzing propagation delays requires extensive data averaging to overcome sampling variability. Here, we use resting-state fMRI data from 11 extensively-sampled individuals to characterize lag structure at the individual level. In addition to stable individual-specific features, we find spatiotemporal topographies in each subject similar to the group average. Notably, we find a set of early regions that are common to all individuals, are preferentially positioned proximal to multiple functional networks, and overlap with brain regions known to respond to diverse behavioral tasks—altogether consistent with a hypothesized ability to broadly influence cortical excitability. Our findings suggest that, like correlation structure, temporal lag structure is a fundamental organizational property of resting-state infra-slow activity.

scholarly journals Altered functional connectivity in default mode network in absence epilepsy: A resting-state fMRI study

2011 ◽  
Vol 32 (3) ◽  
pp. 438-449 ◽  
Author(s):  
Cheng Luo ◽  
Qifu Li ◽  
Yongxiu Lai ◽  
Yang Xia ◽  
Yun Qin ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Default Mode Network ◽  
Resting State ◽  
Resting State Fmri ◽  
Absence Epilepsy ◽  
Default Mode ◽  
Fmri Study

scholarly journals Large-scale DCMs for resting-state fMRI

2017 ◽  
Vol 1 (3) ◽  
pp. 222-241 ◽  
Author(s):  
Adeel Razi ◽  
Mohamed L. Seghier ◽  
Yuan Zhou ◽  
Peter McColgan ◽  
Peter Zeidman ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Large Scale ◽  
Effective Connectivity ◽  
Directed Graphs ◽  
Resting State Fmri ◽  
Causal Modeling ◽  
Large Graphs ◽  
Model Inversion ◽  
Graph Theoretic

This paper considers the identification of large directed graphs for resting-state brain networks based on biophysical models of distributed neuronal activity, that is, effective connectivity. This identification can be contrasted with functional connectivity methods based on symmetric correlations that are ubiquitous in resting-state functional MRI (fMRI). We use spectral dynamic causal modeling (DCM) to invert large graphs comprising dozens of nodes or regions. The ensuing graphs are directed and weighted, hence providing a neurobiologically plausible characterization of connectivity in terms of excitatory and inhibitory coupling. Furthermore, we show that the use of Bayesian model reduction to discover the most likely sparse graph (or model) from a parent (e.g., fully connected) graph eschews the arbitrary thresholding often applied to large symmetric (functional connectivity) graphs. Using empirical fMRI data, we show that spectral DCM furnishes connectivity estimates on large graphs that correlate strongly with the estimates provided by stochastic DCM. Furthermore, we increase the efficiency of model inversion using functional connectivity modes to place prior constraints on effective connectivity. In other words, we use a small number of modes to finesse the potentially redundant parameterization of large DCMs. We show that spectral DCM—with functional connectivity priors—is ideally suited for directed graph theoretic analyses of resting-state fMRI. We envision that directed graphs will prove useful in understanding the psychopathology and pathophysiology of neurodegenerative and neurodevelopmental disorders. We will demonstrate the utility of large directed graphs in clinical populations in subsequent reports, using the procedures described in this paper.

scholarly journals Reduced Default Mode Network Functional Connectivity in Patients with Recurrent Major Depressive Disorder

2018 ◽  
Author(s):  
Chao-Gan Yan ◽  
Xiao Chen ◽  
Le Li ◽  
Francisco Xavier Castellanos ◽  
Tong-Jian Bai ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Functional Connectivity ◽  
Depressive Disorder ◽  
Default Mode Network ◽  
Resting State ◽  
Resting State Fmri ◽  
Research Groups ◽  
Major Depressive ◽  
Default Mode ◽  
Normal Controls

ABSTRACTMajor Depressive Disorder (MDD) is common and disabling, but its neuropathophysiology remains unclear. Most studies of functional brain networks in MDD have had limited statistical power and data analysis approaches have varied widely. The REST-meta-MDD Project of resting-state fMRI (R-fMRI) addresses these issues. Twenty-five research groups in China established the REST-meta-MDD Consortium by contributing R-fMRI data from 1,300 patients with MDD and 1,128 normal controls (NCs). Data were preprocessed locally with a standardized protocol prior to aggregated group analyses. We focused on functional connectivity (FC) within the default mode network (DMN), frequently reported to be increased in MDD. Instead, we found decreased DMN FC when we compared 848 patients with MDD to 794 NCs from 17 sites after data exclusion. We found FC reduction only in recurrent MDD, not in first-episode drug-naïve MDD. Decreased DMN FC was associated with medication usage but not with MDD duration. DMN FC was also positively related to symptom severity but only in recurrent MDD. Exploratory analyses also revealed alterations in FC of visual, sensory-motor and dorsal attention networks in MDD. We confirmed the key role of DMN in MDD but found reduced rather than increased FC within the DMN. Future studies should test whether decreased DMN FC mediates response to treatment. Finally, all resting-state fMRI indices of data contributed by the REST-meta-MDD consortium are being shared publicly via the R-fMRI Maps Project.SIGNIFICANCE STATEMENTFunctional connectivity within the default mode network in major depressive disorder patients has been frequently reported abnormal but with contradicting directions in previous small sample size studies. In creating the REST-meta-MDD consortium containing neuroimaging data of 1,300 depressed patients and 1,128 normal controls from 25 research groups in China, we found decreased default mode network functional connectivity in depressed patients, driven by patients with recurrent depression, and associated with current medication treatment but not with disease duration. These findings suggest that default mode network functional connectivity remains a prime target for understanding the pathophysiology of depression, with particular relevance to revealing mechanisms of effective treatments.

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