Aberrant “Default Mode” Functional Connectivity in Schizophrenia

Garrity, Abigail; Pearlson, Godfrey D.; McKiernan, K.A.; Lloyd, Dan; Kiehl, Kent A.; Calhoun, Vince D.

doi:10.1176/ajp.2007.164.3.450

Cited by 900 publications

(723 citation statements)

References 44 publications

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“…Aberrant functional connectivity in the default mode network has also been identified in patients with schizophrenia [64,65] as well as those at high genetic risk [66]. In the current study, using the mPFC and PCC as seed regions of the DMN, we identified negative correlations between total deletion burden and connectivity between the PCC and the orbitofrontal cortex and between the mPFC and the bilateral associative visual cortex.…”

Section: Iq -Neuroimaging Correlationssupporting

confidence: 51%

Copy number deletion burden is associated with cognitive, structural, and resting-state network differences in patients with schizophrenia

Martin

Robinson

Reutens

et al. 2014

Behavioural Brain Research

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Section: Iq -Neuroimaging Correlationssupporting

confidence: 51%

Copy number deletion burden is associated with cognitive, structural, and resting-state network differences in patients with schizophrenia

Martin

Robinson

Reutens

et al. 2014

Behavioural Brain Research

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“…Many of the high-scoring families consisted of child ROIs with connections to bilateral frontal and temporal lobes, which have been shown using different connectivity measures to be abnormal in schizophrenia patients (Calhoun et al, 2004;Garrity et al, 2007;Winterer et al, 2003). After ICA filtering, the second highest ACL score was found between the cerebellum and dorsal lateral prefrontal cortex, which suggests that this connection might be impaired in patients with schizophrenia.…”

Section: Discussionmentioning

confidence: 96%

“…Our hypothesis was that the ACL scores for healthy controls would be higher than that of patients, based on previous studies that have shown aberrant connectivity and synchrony in schizophrenia patients (Friston and Frith, 1995;Garrity et al, 2007;Kim et al, 2007;Schlosser et al, 2003). We further hypothesized that the classdiscriminative families found from both the original analyses and the ICA filtered approach would represent significant ROIs that characterize schizophrenia during this auditory paradigm and that these regions would be consistent with previous studies that have implicated areas such as the bilateral temporal lobes, bilateral parietal lobes, thalamus, and cerebellum Kim et al, 2007;Laurens et al, 2005).…”

Section: Introductionmentioning

confidence: 99%

Hybrid ICA–Bayesian network approach reveals distinct effective connectivity differences in schizophrenia

et al. 2008

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We utilized a discrete dynamic Bayesian network (dDBN) approach (Burge et al., 2007) to determine differences in brain regions between patients with schizophrenia and healthy controls on a measure of effective connectivity, termed the approximate conditional likelihood score (ACL) (Burge and Lane, 2005). The ACL score represents a class-discriminative measure of effective connectivity by measuring the relative likelihood of the correlation between brain regions in one group versus another. The algorithm is capable of finding non-linear relationships between brain regions because it uses discrete rather than continuous values and attempts to model temporal relationships with a first-order Markov and stationary assumption constraint (Papoulis, 1991). Since Bayesian networks are overly sensitive to noisy data, we introduced an independent component analysis (ICA) filtering approach that attempted to reduce the noise found in fMRI data by unmixing the raw datasets into a set of independent spatial component maps. Components that represented noise were removed and the remaining components reconstructed into the dimensions of the original fMRI datasets. We applied the dDBN algorithm to a group of 35 patients with schizophrenia and 35 matched healthy controls using an ICA filtered and unfiltered approach. We determined that filtering the data significantly improved the magnitude of the ACL score. Patients showed the greatest ACL scores in several regions, most markedly the cerebellar vermis and hemispheres. Our findings suggest that schizophrenia patients exhibit weaker connectivity than healthy controls in multiple regions, including bilateral temporal and frontal cortices, plus cerebellum during an auditory paradigm.

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“…Functional Activity/Deactivation and Connectivity within the DMN in Schizophrenia Activity/Deactivation in the DMN in Schizophrenia Many fMRI studies have demonstrated abnormal activity or deactivation within the DMN areas in patients with schizophrenia during a broad range of tasks, including the auditory oddball task [36][37][38], multi-source interference task [39], working memory task [40][41][42], selective attention task [43], and semantic repetition priming task [44]. Garrity and colleagues [36] first used fMRI to examine the auditory oddball task effects on the DMN in chronic schizophrenia patients.…”

Section: Anti-correlation With the Task Positive Networkmentioning

confidence: 99%

A Review of the Functional and Anatomical Default Mode Network in Schizophrenia

et al. 2016

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Schizophrenia is a severe mental disorder characterized by impaired perception, delusions, thought disorder, abnormal emotion regulation, altered motor function, and impaired drive. The default mode network (DMN), since it was first proposed in 2001, has become a central research theme in neuropsychiatric disorders, including schizophrenia. In this review, first we define the DMN and describe its functional activity, functional and anatomical connectivity, heritability, and inverse correlation with the task positive network. Second, we review empirical studies of the anatomical and functional DMN, and anti-correlation between DMN and the task positive network in schizophrenia. Finally, we review preliminary evidence about the relationship between antipsychotic medications and regulation of the DMN, review the role of DMN as a treatment biomarker for this disease, and consider the DMN effects of individualized therapies for schizophrenia.

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Aberrant “Default Mode” Functional Connectivity in Schizophrenia

Cited by 900 publications

References 44 publications

Copy number deletion burden is associated with cognitive, structural, and resting-state network differences in patients with schizophrenia

Copy number deletion burden is associated with cognitive, structural, and resting-state network differences in patients with schizophrenia

Hybrid ICA–Bayesian network approach reveals distinct effective connectivity differences in schizophrenia

A Review of the Functional and Anatomical Default Mode Network in Schizophrenia

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