Network-specific cortico-thalamic dysconnection in schizophrenia revealed by intrinsic functional connectivity analyses

Tu, Pei-Chi; Lee, Ying-Chiao; Chen, Ying-Shiue; Hsu, Ju-Wei; Li, Cheng Ta; Su, Tung‐Ping

doi:10.1016/j.schres.2015.05.023

Cited by 35 publications

(23 citation statements)

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“…Patients with schizophrenia show lower global functional connectivity between many regions, including: subcortical regions, the frontal, temporal, and occipital cortices. A replicated exception to this trend is increased functional connectivity between the thalamus and somatosensory and motor areas (Argyelan et al, 2014;Damaraju et al, 2014;Giraldo-Chica and Woodward, 2017;Skudlarski et al, 2010;Tu et al, 2015). The "Disconnection hypothesis" (i.e.…”

Section: Discussionmentioning

confidence: 99%

“…The most reported deficit is lower global functional connectivity between many regions, including: subcortical regions; and the frontal, temporal, and occipital cortices. However, a replicated exception to this trend is increased functional connectivity between the thalamus and somatosensory and motor areas (Argyelan et al, 2014;Damaraju et al, 2014;Giraldo-Chica and Woodward, 2017;Skudlarski et al, 2010;Tu et al, 2015). Reduction in functional connectivity is suggested to be the result of alterations in brain structural connectivity at different levels from impaired synaptic plasticity (Friston, 1998) to reduction in the capacity of the structural connections at macroscale (Kahn et al, 2015;.…”

Section: Schizophreniamentioning

confidence: 99%

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Spatial dynamics within and between brain functional domains: A hierarchical approach to study time-varying brain function

Iraji

Damarajua

et al. 2018

Preprint

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The analysis of time-varying connectivity in functional magnetic resonance imaging (fMRI) has become an important part of ongoing neuroscience discussions. The majority of such studies have focused primarily on temporal variations of functional connectivity among fixed regions of interest (ROIs) or networks of the brain. However, the brain reorganizes its activity on both temporal and spatial scales.Thus an approach which captures time-varying characteristics of brain functional organizations is essential to improving our understanding of brain function. Here, we propose an approach that uses blood oxygenation-level dependent (BOLD) signal to capture spatiotemporal variations of the functional domains of the brain. The approach is based on the well-accepted assumption that the brain can be modeled as a hierarchical functional architecture with different levels of granularity, and as we move to lower levels of this architecture, the complexity associated with each element of this hierarchy decreases.In other words, lower levels have less dynamic behavior and higher functional homogeneity, and there is a level at which its elements can be approximated as "functional units". A functional unit is a pattern of regions with very similar functional activity over time. At the macro-scale, we suggest high-order intrinsic connectivity networks (hICNs) obtained from a high-order spatial independent component analysis (ICA) provide a way to approximate functional units. We consider hICNs to comprise functional domains, elements of a higher level of the brain functional hierarchy which are being investigated in this study. Focusing on time-varying characteristics of functional domains, our approach captures the unique information of each functional domain at every timepoint and has the capacity to examine spatiotemporal variations of the functional domains up to the maximum temporal and spatial resolutions that exist in the data. Here, k-means clustering was deployed to summarize time-varying characteristics of each functional domain into a set of representatives called spatial domain states. Furthermore, the functional connectivity between domains was examined to identify functional modules. Each functional module contains states of functional domains with higher connectivity with each other than with other states. Our proposed approach was further evaluated using a multi-site dataset of resting-state BOLD/fMRI data collected from . CC-BY-ND 4.0 International license It is made available under a (which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint . http://dx.doi.org/10.1101/391094 doi: bioRxiv preprint first posted online Aug. 13, 2018; 3 160 healthy controls and 149 patients with schizophrenia (SZ). The findings demonstrate that functional domains are spatially fluid over time. Results highlight a negative relationship between the default mode domain and the attention domain in functional module 3. The ...

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Section: Discussionmentioning

confidence: 99%

Section: Schizophreniamentioning

confidence: 99%

Spatial dynamics within and between brain functional domains: A hierarchical approach to study time-varying brain function

Iraji

Damarajua

et al. 2018

Preprint

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“…Since the initial studies by Welsh et al, (2010), Woodward et al, (2012), and Anticevic et al, (2014), several other groups have found abnormal thalamic functional connectivity in schizophrenia (Klingner et al, 2014; Tu et al, 2015; Lerman-Sinkoff and Barch, 2016; Atluri et al, 2015; Wang et al, 2015). In almost all cases, the combined pattern of thalamic under-connectivity with PFC and over-connectivity with sensory and motor areas was replicated.…”

Section: 0 Thalamocortical Pathology In Schizophrenia: Contributiomentioning

confidence: 99%

Review of thalamocortical resting-state fMRI studies in schizophrenia

Giraldo‐Chica

Woodward

2017

Schizophrenia Research

188

113

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Brain circuitry underlying cognition, emotion, and perception is abnormal in schizophrenia. There is considerable evidence that the neuropathology of schizophrenia includes the thalamus, a key hub of cortical-subcortical circuitry and an important regulator of cortical activity. However, the thalamus is a heterogeneous structure composed of several nuclei with distinct inputs and cortical connections. Limitations of conventional neuroimaging methods and conflicting findings from post-mortem investigations have made it difficult to determine if thalamic pathology in schizophrenia is widespread or limited to specific thalamocortical circuits. Resting-state fMRI has proven invaluable for understanding the large-scale functional organization of the brain and investigating neural circuitry relevant to psychiatric disorders. This article summarizes resting-state fMRI investigations of thalamocortical functional connectivity in schizophrenia. Particular attention is paid to the course, diagnostic specificity, and clinical correlates of thalamocortical network dysfunction.

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“…The most reported deficit is lower global functional connectivity between many regions, including subcortical regions; and the frontal, temporal, and occipital cortices. However, a replicated exception to this trend is increased functional connectivity between the thalamus and somatosensory and motor areas (Argyelan et al, 2014;Giraldo-Chica & Woodward, 2017;Skudlarski et al, 2010;Tu et al, 2015). Reduction in functional connectivity is suggested to be the result of alterations in brain structural connectivity at different levels from impaired synaptic plasticity (Friston, 1998) to reduction in the capacity of the structural connections at macroscale (Kahn et al, 2015;van den Heuvel, Mandl, Stam, Kahn, & Hulshoff Pol, 2010).…”

Section: Schizophreniamentioning

confidence: 99%

Spatial dynamics within and between brain functional domains: A hierarchical approach to study time‐varying brain function

Iraji

Damaraju

et al. 2018

Human Brain Mapping

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The analysis of time-varying activity and connectivity patterns (i.e., the chronnectome) using resting-state magnetic resonance imaging has become an important part of ongoing neuroscience discussions. The majority of previous work has focused on variations of temporal coupling among fixed spatial nodes or transition of the dominant activity/connectivity pattern over time. Here, we introduce an approach to capture spatial dynamics within functional domains (FD), as well as temporal dynamics within and between FD. The approach models the brain as a hierarchical functional architecture with different levels of granularity, where lower levels have higher functional homogeneity and less dynamic behavior and higher levels have less homogeneity and more dynamic behavior. First, a high-order spatial independent component analysis is used to approximate functional units. A functional unit is a pattern of regions with very similar functional activity over time. Next, functional units are used to construct FDs. Finally, functional modules (FMs) are calculated from FDs, providing an overall view of brain dynamics. Results highlight the spatial fluidity within FDs, including a broad spectrum of changes in regional associations from strong coupling to complete decoupling. Moreover, FMs capture the dynamic interplay between FDs. Patients with schizophrenia show transient reductions in functional activity and state connectivity across several FDs, particularly the subcortical domain. Activity and connectivity differences convey unique information in many cases (e.g. the default mode) highlighting their complementarity information. The proposed hierarchical model to capture FD spatiotemporal variation provides new insight into the macroscale chronnectome and identifies changes hidden from existing approaches.

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Network-specific cortico-thalamic dysconnection in schizophrenia revealed by intrinsic functional connectivity analyses

Cited by 35 publications

References 53 publications

Spatial dynamics within and between brain functional domains: A hierarchical approach to study time-varying brain function

Spatial dynamics within and between brain functional domains: A hierarchical approach to study time-varying brain function

Review of thalamocortical resting-state fMRI studies in schizophrenia

Spatial dynamics within and between brain functional domains: A hierarchical approach to study time‐varying brain function

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