Temporal-thalamic and cingulo-opercular connectivity in people with schizophrenia

Culbreth, Adam J.; Wu, Qiong; Chen, Shuo; Adhikari, Bhim M.; Hong, L. Elliot; Gold, James M.; Waltz, James A.

doi:10.1016/j.nicl.2020.102531

Cited by 10 publications

(9 citation statements)

References 66 publications

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“… 7–11 Over the past 2 decades, neuroimaging studies have identified widespread functional dysconnectivity in individuals with schizophrenia relative to controls. 12–18 These findings have led to the conclusion that schizophrenia cannot be explained in terms of localized dysfunction within specific brain areas and is better understood as a disruption of network-level functional organization. 19–22 The study of functional brain organization has the potential to identify predictive biomarkers for neurodevelopmental and neuropsychiatric disorders and shed light on their underlying mechanisms.…”

Section: Introductionmentioning

confidence: 99%

Graph Convolutional Networks Reveal Network-Level Functional Dysconnectivity in Schizophrenia

Lei

Donohoe

Lui

et al. 2022

Schizophrenia Bulletin

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Background and Hypothesis Schizophrenia is increasingly understood as a disorder of brain dysconnectivity. Recently, graph-based approaches such as graph convolutional network (GCN) have been leveraged to explore complex pairwise similarities in imaging features among brain regions, which can reveal abstract and complex relationships within brain networks. Study Design We used GCN to investigate topological abnormalities of functional brain networks in schizophrenia. Resting-state functional magnetic resonance imaging data were acquired from 505 individuals with schizophrenia and 907 controls across 6 sites. Whole-brain functional connectivity matrix was extracted for each individual. We examined the performance of GCN relative to support vector machine (SVM), extracted the most salient regions contributing to both classification models, investigated the topological profiles of identified salient regions, and explored correlation between nodal topological properties of each salient region and severity of symptom. Study Results GCN enabled nominally higher classification accuracy (85.8%) compared with SVM (80.9%). Based on the saliency map, the most discriminative brain regions were located in a distributed network including striatal areas (ie, putamen, pallidum, and caudate) and the amygdala. Significant differences in the nodal efficiency of bilateral putamen and pallidum between patients and controls and its correlations with negative symptoms were detected in post hoc analysis. Conclusions The present study demonstrates that GCN allows classification of schizophrenia at the individual level with high accuracy, indicating a promising direction for detection of individual patients with schizophrenia. Functional topological deficits of striatal areas may represent a focal neural deficit of negative symptomatology in schizophrenia.

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Section: Introductionmentioning

confidence: 99%

Graph Convolutional Networks Reveal Network-Level Functional Dysconnectivity in Schizophrenia

Lei

Donohoe

Lui

et al. 2022

Schizophrenia Bulletin

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show abstract

“…The thalamus is an important brain region for information transmission, integration, and pain modulation ( Ploner et al, 2010 ). Specifically, the nostalgia-encoding region within the prefrontal thalamus is the thalamic subregion connected to the prefrontal lobe ( Garibotto et al, 2020 ; Culbreth et al, 2021 ), which is known to be critical for higher cognitive functions ( Mitchell, 2015 ). In contrast, analgesia encoding within the posterior parietal thalamus involves the thalamic subregion connected to the posterior parietal lobe ( Liu et al, 2019 ; Garibotto et al, 2020 ), contributing to multisensory and sensory-motor integration ( Gilissen et al, 2021 ).…”

Section: Discussionmentioning

confidence: 99%

Thalamocortical Mechanisms for Nostalgia-Induced Analgesia

et al. 2022

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As a predominately positive emotion, nostalgia serves various adaptive functions, including a recently revealed analgesic effect. The current fMRI study aimed to explore the neural mechanisms underlying the nostalgia-induced analgesic effect on noxious thermal stimuli of different intensities. Human participants' (males and females) behavior results showed that the nostalgia paradigm significantly reduced participants' perception of pain, particularly at low pain intensities. fMRI analysis revealed that analgesia was related to decreased brain activity in pain-related brain regions, including the lingual and parahippocampal gyrus. Notably, anterior thalamic activation during the nostalgia stage predicted posterior parietal thalamus activation during the pain stage, suggesting that the thalamus might play a key role as a central functional linkage in the analgesic effect. Moreover, while thalamus-PAG functional connectivity was found to be related to nostalgic strength, periaqueductal gray-dorsolateral prefrontal cortex (PAG-dlPFC) functional connectivity was found to be associated with pain perception, suggesting possible analgesic modulatory pathways. These findings demonstrate the analgesic effect of nostalgia and, more importantly, shed light on its neural mechanism. SIGNIFICANCE STATEMENT Nostalgia is known to reduce individuals' perception of physical pain. The underlying brain mechanisms, however, are unclear. Our study found that the thalamus plays a key role as a functional linkage between nostalgia and pain, suggesting a possible analgesic modulatory mechanism of nostalgia. These findings have implications for the underlying brain mechanisms of psychological analgesia.

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“…Currently, thalamocortical dysconnectivity consisting of reduced thalamo-prefrontal and increased thalamo-somatosensory/parietal connectivity is considered a core neurobiological abnormality in schizophrenia [for further reading, see ( 23 , 30 , 31 )]. Recently developed methods to investigate the interconnectivity of the thalamus, cerebellum, and cortex revealed dysconnectivity among the thalamus, cerebellum, and temporal cortex ( 32 , 33 , 34 ), which highlights the widespread involvement of the thalamus in brain activity and suggests the cerebellum as the next key region to investigate.…”

Section: Thalamic Connectivity System Abnormalities In Psychiatric Di...mentioning

confidence: 99%

Thalamic Connectivity System Across Psychiatric Disorders: Current Status and Clinical Implications

Hwang

Kwak

Cho

et al. 2022

Biological Psychiatry Global Open Science

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Temporal-thalamic and cingulo-opercular connectivity in people with schizophrenia

Abstract: Highlights People with schizophrenia show increased thalamo-temporal functional connectivity. People with schizophrenia also show reduced cingulo-opercular connectivity. Thalamo-temporal findings appear robust, replicating across two samples.

Cited by 10 publications

References 66 publications

Graph Convolutional Networks Reveal Network-Level Functional Dysconnectivity in Schizophrenia

Graph Convolutional Networks Reveal Network-Level Functional Dysconnectivity in Schizophrenia

Thalamocortical Mechanisms for Nostalgia-Induced Analgesia

Thalamic Connectivity System Across Psychiatric Disorders: Current Status and Clinical Implications

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