The disconnection hypothesis

Friston, Karl J.

doi:10.1016/s0920-9964(97)00140-0

Cited by 790 publications

(557 citation statements)

References 43 publications

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“…Furthermore, the excellent temporal precision afforded by MEG allows estimation of dynamic changes in network structure Brookes et al, 2014;O'Neill et al, 2015a). The importance of characterising electrophysiological connectivity is growing, with numerous demonstrations that connections are perturbed in pathologies Friston, 1998;Guggisberg et al, 2008;Kessler et al, 2014;Palaniyappan and Liddle, 2012;Schnitzler and Gross, 2005;Stufflebeam et al, 2011;Tewarie et al, 2014;van Dellen et al, 2012). However, demonstrations have typically been made on large subject groups, with little attention paid to the accuracy of measurements within individual subjects.…”

Section: Introductionmentioning

confidence: 99%

Optimising experimental design for MEG resting state functional connectivity measurement

et al. 2017

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The study of functional connectivity using magnetoencephalography (MEG) is an expanding area of neuroimaging, and adds an extra dimension to the more common assessments made using fMRI. The importance of such metrics is growing, with recent demonstrations of their utility in clinical research, however previous reports suggest that whilst group level resting state connectivity is robust, single session recordings lack repeatability. Such robustness is critical if MEG measures in individual subjects are to prove clinically valuable. In the present paper, we test how practical aspects of experimental design affect the intra-subject repeatability of MEG findings; specifically we assess the effect of coregistration method and data recording duration. We show that the use of a foam head-cast, which is known to improve coregistration accuracy, increased significantly the between session repeatability of both beamformer reconstruction and connectivity estimation. We also show that recording duration is a critical parameter, with large improvements in repeatability apparent when using ten minute, compared to five minute recordings. Further analyses suggest that the origin of this latter effect is not underpinned by technical aspects of source reconstruction, but rather by a genuine effect of brain state; short recordings are simply inefficient at capturing the canonical MEG network in a single subject. Our results provide important insights on experimental design and will prove valuable for future MEG connectivity studies.3

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Section: Introductionmentioning

confidence: 99%

Optimising experimental design for MEG resting state functional connectivity measurement

et al. 2017

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“…Previous research suggests that the complex clinical presentations (psychotic symptoms and cognitive alterations) of schizophrenia may be related to abnormal integration between spatially distinct brain areas and inefficient information processing (Bullmore et al. 1997; Friston 1998; Stephan et al. 2006; Wang et al.…”

Section: Introductionmentioning

confidence: 99%

Reduced specialized processing in psychotic disorder: a graph theoretical analysis of cerebral functional connectivity

et al. 2016

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BackgroundPrevious research has shown that the human brain can be represented as a complex functional network that is characterized by specific topological properties, such as clustering coefficient, characteristic path length, and global/local efficiency. Patients with psychotic disorder may have alterations in these properties with respect to controls, indicating altered efficiency of network organization. This study examined graph theoretical changes in relation to differential genetic risk for the disorder and aimed to identify clinical correlates.MethodsAnatomical and resting‐state MRI brain scans were obtained from 73 patients with psychotic disorder, 83 unaffected siblings, and 72 controls. Topological measures (i.e., clustering coefficient, characteristic path length, and small‐worldness) were used as dependent variables in a multilevel random regression analysis to investigate group differences. In addition, associations with (subclinical) psychotic/cognitive symptoms were examined.ResultsPatients had a significantly lower clustering coefficient compared to siblings and controls, with no difference between the latter groups. No group differences were observed for characteristic path length and small‐worldness. None of the topological properties were associated with (sub)clinical psychotic and cognitive symptoms.ConclusionsThe reduced ability for specialized processing (reflected by a lower clustering coefficient) within highly interconnected brain regions observed in the patient group may indicate state‐related network alterations. There was no evidence for an intermediate phenotype and no evidence for psychopathology‐related alterations.

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“…These observations "underscore the importance of evaluating white matter fiber tract abnormalities in schizophrenia" (Kubicki et al, 2005) which may contribute to the hypothesized disordered connectivity between brain regions in schizophrenia (Friston, 1998). A number of recent studies have applied diffusion tensor imaging (DTI), a magnetic resonance imaging method sensitive to white matter integrity, to the study of schizophrenia; using the apparent diffusion coefficient (ADC) or fractional anisotropy (FA) measures, the majority of these find white matter deficits associated with the disease (Kubicki et al, 2007;Mori et al, 2007;Shergill et al, 2007;Buchsbaum et al, 2006;Rose et al, 2006;Jones et al, 2005b;Kitamura et al, 2005;Kubicki et al, 2005;Kanaan et al, 2005;Kumra et al, 2005;Szeszko et al, 2005).…”

Section: Introductionmentioning

confidence: 99%

Diffusion tensor imaging in schizophrenia: Relationship to symptoms

Skelly

Calhoun

Meda

et al. 2008

Schizophrenia Research

117

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In this diffusion tensor imaging (DTI) study, the authors investigated white matter integrity in schizophrenia and the relationships between white matter alterations and specific symptoms of the disorder. We compared DTI images of 25 schizophrenia patients and 25 matched healthy controls and performed voxel-wise correlational analyses using the patient's DTI data and their severity scores of positive and negative symptoms. We found diffuse deficits in multiple types of white matter tracts in schizophrenia, and an inverse relationship of DTI fractional anisotropy (FA) values with positive symptom scores in association fibers, supporting a "disconnection" hypothesis of positive symptoms in schizophrenia.

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The disconnection hypothesis

Cited by 790 publications

References 43 publications

Optimising experimental design for MEG resting state functional connectivity measurement

Optimising experimental design for MEG resting state functional connectivity measurement

Reduced specialized processing in psychotic disorder: a graph theoretical analysis of cerebral functional connectivity

Diffusion tensor imaging in schizophrenia: Relationship to symptoms

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