Disruptive changes of cerebellar functional connectivity with the default mode network in schizophrenia

Wang, Lubin; Zou, Feng; Shao, Yuanyuan; Ye, Enmao; Xiao, Jin; Shuwen, Tan; Hu, Dewen; Zheng, Yang

doi:10.1016/j.schres.2014.09.034

Cited by 70 publications

(48 citation statements)

References 49 publications

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“…Further, crus I and II abnormalities have been associated with deficits in integrating and regulating emotional and cognitive functions (Igloi et al, 2014; Riva et al, 2013). As such, our findings are consistent with previous studies showing crus involvement in the spontaneous brain activity of the DMN (Krienen and Buckner, 2009; Wang et al, 2014), and weaker connectivity strength between the PCC and Crus I/II could underlie the cognitive and emotional deficits associated with cannabis use disorder and tobacco use disorder. It is important to note that we did not observe differences in PCC-Crus connectivity strength among CTs relative to HCs; however, differences emerged when the statistical threshold was reduced (i.e., p < 0.005, uncorrected).…”

Section: Discussionsupporting

confidence: 93%

“…In both C and T groups, lower connectivity was observed between the PCC and bilateral regions of crus I and crus II. Interestingly, recent functional connectivity analyses using the crus I as a seed region found significant correlated activity between the crus I and the mPFC, the inferior parietal cortex, and the PCC (Krienen and Buckner, 2009; Wang et al, 2014). Further, crus I and II abnormalities have been associated with deficits in integrating and regulating emotional and cognitive functions (Igloi et al, 2014; Riva et al, 2013).…”

Section: Discussionmentioning

confidence: 99%

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Cannabis, cigarettes, and their co-occurring use: Disentangling differences in default mode network functional connectivity

Wetherill

Fang

Jagannathan

et al. 2015

Drug and Alcohol Dependence

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Background Resting-state functional connectivity is a noninvasive, neuroimaging method for assessing neural network function. Altered functional connectivity among regions of the default-mode network have been associated with both nicotine and cannabis use; however, less is known about co-occurring cannabis and tobacco use. Methods We used posterior cingulate cortex (PCC) seed-based resting-state functional connectivity analyses to examine default mode network (DMN) connectivity strength differences between four groups: 1) individuals diagnosed with cannabis dependence who do not smoke tobacco (n=19; ages 20–50), 2) cannabis-dependent individuals who smoke tobacco (n=23, ages 21–52), 3) cannabis-naïve, nicotine-dependent individuals who smoke tobacco (n=24, ages 21–57), and 4) cannabis- and tobacco-naïve healthy controls (n=21, ages 21–50), controlling for age, sex, and alcohol use. We also explored associations between connectivity strength and measures of cannabis and tobacco use. Results PCC seed-based analyses identified the core nodes of the DMN (i.e., PCC, medial prefrontal cortex, inferior parietal cortex, and temporal cortex). In general, the cannabis-dependent, nicotine-dependent, and co-occurring use groups showed lower DMN connectivity strengths than controls, with unique group differences in connectivity strength between the PCC and the cerebellum, medial prefrontal cortex, parahippocampus, and anterior insula. In cannabis-dependent individuals, PCC-right anterior insula connectivity strength correlated with duration of cannabis use. Conclusions This study extends previous research that independently examined the differences in resting-state functional connectivity among individuals who smoke cannabis and tobacco by including an examination of co-occurring cannabis and tobacco use and provides further evidence that cannabis and tobacco exposure is associated with alterations in DMN connectivity.

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Section: Discussionsupporting

confidence: 93%

Section: Discussionmentioning

confidence: 99%

Cannabis, cigarettes, and their co-occurring use: Disentangling differences in default mode network functional connectivity

Wetherill

Fang

Jagannathan

et al. 2015

Drug and Alcohol Dependence

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“…Interestingly, when considering our finding of increased functional connectivity within the entire thalamo-cortico-cerebellar network, it also aligns with previous studies that showed alterations in thalamo-cortico-cerebellar circuits: increased connectivity between thalamus and multiple sensory areas, and decreased connectivity between thalamus and the cerebellum 32,45 , cerebellar region showed increased connectivity with the prefrontal cortex and thalamus as well as decreased connectivity with the visual cortex and sensorimotor cortex 35 , dysconnections in cognition-related resting state networks 46 , and reduced functional connectivity in a thalamocortico-cerebellar network 33,34,47 .…”

Section: Nbs the Application Of Nbs On Previously Calculated Functiosupporting

confidence: 88%

Altered resting state functional connectivity in a thalamo-cortico-cerebellar network in patients with schizophrenia

Klock

Baechle

et al. 2018

Preprint

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Schizophrenia is described as a disease in which complex psychopathology together with cognitive and behavioral impairments are related to widely disrupted brain circuitry causing a failure in coordinating information across multiple brain sites. This led to the hypothesis of schizophrenia as a network disease e.g. in the cognitive dysmetria model and the dysconnectivity theory. Nevertheless, there is no consensus regarding localized mechanisms, namely dysfunction of certain networks underlying the multifaceted symptomatology.In this study, we investigated potential functional disruptions in 35 schizophrenic patients and 41controls using complex cerebral network analysis, namely network-based statistic (NBS) and graph theory in resting state fMRI. NBS can reveal locally impaired subnetworks whereas graph analysis characterizes whole brain network topology.Using NBS we observed a local hyperconnected thalamo-cortico-cerebellar subnetwork in the schizophrenia group. Furthermore, nodal graph measures retrieved from the thalamo-corticocerebellar subnetwork revealed that the total number of connections from/to (degree) of the thalamus is higher in patients with schizophrenia. Interestingly, graph analysis on the whole brain functional networks did not reveal group differences. Together, our results suggest that disruptions in the brain networks of schizophrenia patients are situated at the local level of the hyperconnected thalamo-cortico-cerebellar rather than globally spread in brain.Our results provide further evidence for the importance of the thalamus and cerebellum in schizophrenia and to the notion that schizophrenia is a network disease in line with the dysconnectivity theory and cognitive dysmetria model.

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“…In schizophrenia (SZ), cerebellar abnormalities have been observed in terms of brain structure and function [7][8][9][10]. The majority of functional studies focused on changes in the cortico-cerebellar-thalamic-cortical circuit (CCTCC) as put forward by the concept of "cognitive dysmetria", e. g. [11][12][13][14][15]. This model suggests that cognitive abilities, similar to motor functions, are supported by a CCTCC feedback loop that normally monitors and controls mental activity.…”

Section: Introductionmentioning

confidence: 99%

Abnormal cerebellar volume in somatic vs. non-somatic delusional disorders

et al. 2020

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Background: There is abundant evidence for cerebellar involvement in schizophrenia, where the cerebellum has been suggested to contribute to cognitive, affective and motor dysfunction. More recently, specific cerebellar regions have also been associated with psychotic symptoms, particularly with auditory verbal hallucinations. In contrast, little is known about cerebellar contributions to delusions, and even less is known about whether cerebellar involvement differs by delusional content. Methods: Using structural magnetic resonance imaging at 1.0 T together with cerebellum-optimized segmentation techniques, we investigated gray matter volume (GMV) in 14 patients with somatic-type delusional disorder (S-DD), 18 patients with non-somatic delusional disorder (NS-DD) and 18 patients with schizophrenia (SZ) with persistent non-somatic delusions. A total of 32 healthy controls (HC) were included. Between-group comparisons were adjusted for age, gender, chlorpromazine equivalents and illness duration. Results: Compared to HC, S-DD patients showed decreased GMV in left lobule VIIIa. In addition, S-DD patients showed decreased GMV in lobule V and increased GMV in bilateral lobule VIIa/crus II compared to NS-DD. Patients with SZ showed increased GMV in right lobule VI and VIIa/crus I compared to HC. Significant differences between HC and NS-DD were not found. Conclusions: The data support the notion of cerebellar dysfunction in psychotic disorders. Distinct cerebellar deficits, predominantly linked to sensorimotor processing, may be detected in delusional disorders presenting with predominantly somatic content.

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Disruptive changes of cerebellar functional connectivity with the default mode network in schizophrenia

Cited by 70 publications

References 49 publications

Cannabis, cigarettes, and their co-occurring use: Disentangling differences in default mode network functional connectivity

Cannabis, cigarettes, and their co-occurring use: Disentangling differences in default mode network functional connectivity

Altered resting state functional connectivity in a thalamo-cortico-cerebellar network in patients with schizophrenia

Abnormal cerebellar volume in somatic vs. non-somatic delusional disorders

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