LOGIN TO YOUR ACCOUNT

Username
Password
Remember Me
Or use your Academic/Social account:

CREATE AN ACCOUNT

Or use your Academic/Social account:

Congratulations!

You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.

Important!

Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message

CREATE AN ACCOUNT

Name:
Username:
Password:
Verify Password:
E-mail:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Lord, Louis-David; Allen, Paul (Researcher in psychiatry); Expert, Paul; Howes, Oliver (Oliver D.); Broome, Matthew R.; Lambiotte, Renaud; Fusar-Poli, Paolo; Valli, Isabel; McGuire, Philip; Turkheimer, Federico E. (2012)
Publisher: Elsevier BV
Languages: English
Types: Article
Subjects: RC0321
Individuals with an at-risk mental state (ARMS) have a risk of developing a psychotic disorder significantly greater than the general population. However, it is not currently possible to predict which ARMS individuals will develop psychosis from clinical assessment alone. Comparison of ARMS subjects who do, and do not, develop psychosis can reveal which factors are critical for the onset of illness. In the present study, 37 patients with an ARMS were followed clinically at least 24 months subsequent to initial referral. Functional MRI data were collected at the beginning of the follow-up period during performance of an executive task known to recruit frontal lobe networks and to be impaired in psychosis. Graph theoretical analysis was used to compare the organization of a functional brain network in ARMS patients who developed a psychotic disorder following the scan (ARMS-T) to those who did not become ill during the same follow-up period (ARMS-NT) and aged-matched controls. The global properties of each group's representative network were studied (density, efficiency, global average path length) as well as regionally-specific contributions of network nodes to the organization of the system (degree, farness-centrality, betweenness-centrality). We focused our analysis on the dorsal anterior cingulate cortex (ACC), a region known to support executive function that is structurally and functionally impaired in ARMS patients. In the absence of between-group differences in global network organization, we report a significant reduction in the topological centrality of the ACC in the ARMS-T group relative to both ARMS-NT and controls. These results provide evidence that abnormalities in the functional organization of the brain predate the onset of psychosis, and suggest that loss of ACC topological centrality is a potential biomarker for transition to psychosis.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • Alexander-Bloch, A.F., Gogtay, N., Meunier, D., Birn, R., Clasen, L., Lalonde, F., Lenroot, R., Giedd, J., Bullmore, E.T., 2010. Disrupted modularity and local connectivity of brain functional networks in childhood-onset schizophrenia. Frontiers in Systems Neuroscience 4, 147.
    • Alexander-Bloch, A.F., Vertes, P.E., Stidd, R., Lalonde, F., Clasen, L., Rapoport, J., Giedd, J., Bullmore, E.T., Gogtay, N., 2012. The Anatomical Distance of Functional Connections Predicts Brain Network Topology in Health and Schizophrenia. Cerebral Cortex. http://dx.doi.org/10.1093/cercor/bhr388.
    • Allen, P., Howes, O., Egerton, A., Kazuyuki, H., Valli, I., Kambeitz, J., Fusar-Poli, P., Broome, M., McGuire, P., 2012. Transition to psychosis associated with prefrontal and subcortical dysfunction in ultra high-risk individuals. Schizophrenia Bulletin. http://dx.doi.org/10.1093/schbul/sbr194. ([Epub ahead of print] PubMed PMID: 22290265).
    • Bassett, D.S., Bullmore, E., Verchinski, B.A., Mattay, V.S., Weinberger, D.R., MeyerLindenberg, A., 2008. Hierarchical organization of human cortical networks in health and schizophrenia. Journal of Neuroscience 28, 9239-9248.
    • Borgwardt, S.J., Riecher-Rossler, A., Dazzan, P., Chitnis, X., Aston, J., Drewe, M., Gschwandtner, U., Haller, S., Pfluger, M., Rechsteiner, E., et al., 2007. Regional gray matter volume abnormalities in the at risk mental state. Biological Psychiatry 61, 1148-1156.
    • Borgwardt, S.J., McGuire, P.K., Aston, J., Gschwandtner, U., Pfluger, M.O., Stieglitz, R.D., Radue, E.W., Riecher-Rossler, A., 2008. Reductions in frontal, temporal and parietal volume associated with the onset of psychosis. Schizophrenia Research 106, 108-114.
    • Broome, M.R., Matthiasson, P., Fusar-Poli, P., Woolley, J.B., Johns, L.C., Tabraham, P., Bramon, E., Valmaggia, L., Williams, S.C., Brammer, M.J., et al., 2009. Neural correlates of executive function and working memory in the 'at-risk mental state'. The British Journal of Psychiatry 194, 25-33.
    • Bullmore, E., Sporns, O., 2009. Complex brain networks: graph theoretical analysis of structural and functional systems. Nature Reviews Neuroscience 10, 186-198.
    • Eastvold, A.D., Heaton, R.K., Cadenhead, K.S., 2007. Neurocognitive deficits in the (putative) prodrome and first episode of psychosis. Schizophrenia Research 93, 266-277.
    • Fornito, A., Yung, A.R., Wood, S.J., Phillips, L.J., Nelson, B., Cotton, S., Velakoulis, D., McGorry, P.D., Pantelis, C., Yucel, M., 2008. Anatomic abnormalities of the anterior cingulate cortex before psychosis onset: an MRI study of ultra-high-risk individuals. Biological Psychiatry 64, 758-765.
    • Fornito, A., Yoon, J., Zalesky, A., Bullmore, E.T., Carter, C.S., 2011. General and specific functional connectivity disturbances in first-episode schizophrenia during cognitive control performance. Biological Psychiatry 70, 64-72.
    • Freeman, L., 1977. A set of measures of centrality based on betweenness. Sociometry 40, 35-41.
    • Freeman, L., 1979. Centrality in social networks: conceptual clarification. Social Networks 1, 215-239.
    • Friston, K.J., 2002. Dysfunctional connectivity in schizophrenia. World Psychiatry 1, 66-71.
    • Friston, K., Holmes, A., Worsley, K., 1999. How many subjects constitute a study? NeuroImage 10 (1), 1-5.
    • Fusar-Poli, P., Perez, J., Broome, M., Borgwardt, S., Placentino, A., Caverzasi, E., Cortesi, M., Veggiotti, P., Politi, P., Barale, F., et al., 2007. Neurofunctional correlates of vulnerability to psychosis: a systematic review and meta-analysis. Neuroscience and Biobehavioral Reviews 31, 465-484.
    • Fusar-Poli, P., Howes, O.D., Allen, P., Broome, M., Valli, I., Asselin, M.C., Grasby, P.M., McGuire, P.K., 2010. Abnormal frontostriatal interactions in people with prodromal signs of psychosis: a multimodal imaging study. Archives of General Psychiatry 67, 683-691.
    • Fusar-Poli, P., Borgwardt, S., Crescini, A., Deste, G., Kempton, M.J., Lawrie, S., Mc Guire, P., Sacchetti, E., 2011. Neuroanatomy of vulnerability to psychosis: a voxel-based meta-analysis. Neuroscience and Biobehavioral Reviews 35, 1175-1185.
    • Fusar-Poli, P., Bonoldi, I., Yung, A.R., Borgwardt, S., Kempton, M.J., Valmaggia, L., Barale, F., Caverzasi, E., McGuire, P., 2012a. Predicting psychosis: meta-analysis of transition outcomes in individuals at high clinical risk. Archives of General Psychiatry 69, 220-229.
    • Fusar-Poli, P., McGuire, P., Borgwardt, S., 2012b. Mapping prodromal psychosis: a critical review of neuroimaging studies. European Psychiatry 27, 181-191.
    • Fusar-Poli, P., Deste, G., Smieskova, R., Barlati, G., Yung, A.R., Howes, O., Stieglitz, R., Vita, A., Mc Guire, P., Borgwardt, S., 2012c. Cognitive functioning in prodromal psychosis: a meta-analysis. Arch Gen Psychiatry 69 (6), 562-571.
    • Hampson, M., Peterson, B.S., Skudlarski, P., Gatenby, J.C., Gore, J.C., 2002. Detection of functional connectivity using temporal correlations in MR images. Human Brain Mapping 15 (4), 247-262.
    • Hawkins, K.A., Addington, J., Keefe, R.S., Christensen, B., Perkins, D.O., Zipurksy, R., Woods, S.W., Miller, T.J., Marquez, E., Breier, A., et al., 2004. Neuropsychological status of subjects at high risk for a first episode of psychosis. Schizophrenia Research 67, 115-122.
    • Hill, K., Mann, L., Laws, K.R., Stephenson, C.M., Nimmo-Smith, I., McKenna, P.J., 2004. Hypofrontality in schizophrenia: a meta-analysis of functional imaging studies. Acta Psychiatrica Scandinavica 110, 243-256.
    • Honey, C.J., Sporns, O., 2008. Dynamical consequences of lesions in cortical networks. Human Brain Mapping 29, 802-809.
    • Hwang, Y., 2010. Comparisons of estimators of the number of true null hypotheses and adaptive FDR procedures on multiplicity testing. Journal of Statistical Computation and Simulation 1563-5163.
    • Jenkinson, M., Bannister, P., Brady, M., Smith, S., 2002. Improved optimization for the robust and accurate linear registration and motion correction of brain images. NeuroImage 17, 825-841.
    • Kay, S.R., Fiszbein, A., Opler, L.A., 1987. The positive and negative syndrome scale (PANSS) for schizophrenia. Schizophrenia Bulletin 13, 261-276.
    • Koutsouleris, N., Schmitt, G.J., Gaser, C., Bottlender, R., Scheuerecker, J., McGuire, P., Burgermeister, B., Born, C., Reiser, M., Moller, H.J., et al., 2009. Neuroanatomical correlates of different vulnerability states for psychosis and their clinical outcomes. The British Journal of Psychiatry 195, 218-226.
    • Liu, Y., Liang, M., Zhou, Y., He, Y., Hao, Y., Song, M., Yu, C., Liu, H., Liu, Z., Jiang, T., 2008. Disrupted small-world networks in schizophrenia. Brain 131, 945-961.
    • Lord, L.D., Allen, P., Expert, P., Howes, O., Lambiotte, R., McGuire, P., Bose, S.K., Hyde, S., Turkheimer, F.E., 2011. Characterization of the anterior cingulate's role in the atrisk mental state using graph theory. NeuroImage 56, 1531-1539.
    • Lynall, M.E., Bassett, D.S., Kerwin, R., McKenna, P.J., Kitzbichler, M., Muller, U., Bullmore, E., 2010. Functional connectivity and brain networks in schizophrenia. Journal of Neuroscience 30, 9477-9487.
    • Minati, L., Grisoli, M., Seth, A.K., Critchley, H.D., 2012. Decision-making under risk: a graph-based network analysis using functional MRI. NeuroImage 60, 2191-2205.
    • Nelson, H., 1982. National Adult Reading Test (NART). NERT, Windsor.
    • Nelson, B., Yung, A.R., 2010. Can clinicians predict psychosis in an ultra high risk group? The Australian and New Zealand Journal of Psychiatry 44, 625-630.
    • Nicol, R.M., Chapman, S.C., Vertes, P.E., Nathan, P.J., Smith, M.L., Shtyrov, Y., Bullmore, E.T., 2012. Fast reconfiguration of high-frequency brain networks in response to surprising changes in auditory input. Journal of Neurophysiology 107, 1421-1430.
    • Pantelis, C., Velakoulis, D., McGorry, P.D., Wood, S.J., Suckling, J., Phillips, L.J., Yung, A.R., Bullmore, E.T., Brewer, W., Soulsby, B., et al., 2003a. Neuroanatomical abnormalities before and after onset of psychosis: a cross-sectional and longitudinal MRI comparison. Lancet 361, 281-288.
    • Pantelis, C., Yucel, M., Wood, S.J., McGorry, P.D., Velakoulis, D., 2003b. Early and late neurodevelopmental disturbances in schizophrenia and their functional consequences. The Australian and New Zealand Journal of Psychiatry 37, 399-406.
    • Pettersson-Yeo, W., Allen, P., Benetti, S., McGuire, P., Mechelli, A., 2010. Dysconnectivity in schizophrenia: where are we now? Neuroscience and Biobehavioral Reviews 35, 1110-1124.
    • Power, J.D., Barnes, K.A., Snyder, A.Z., Schlaggar, B.L., Petersen, S.E., 2012. Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. NeuroImage 59, 2142-2154.
    • Rothlisberger, M., Riecher-Rossler, A., Aston, J., Fusar-Poli, P., Radu, E.W., Borgwardt, S., 2012. Cingulate volume abnormalities in emerging psychosis. Current Pharmaceutical Design 18, 495-504.
    • Sabb, F.W., van Erp, T.G., Hardt, M.E., Dapretto, M., Caplan, R., Cannon, T.D., Bearden, C.E., 2010. Language network dysfunction as a predictor of outcome in youth at clinical high risk for psychosis. Schizophrenia Research 116, 173-183.
    • Salvador, R., Suckling, J., Coleman, M.R., Pickard, J.D., Menon, D., Bullmore, E., 2005. Neurophysiological architecture of functional magnetic resonance images of human brain. Cerebral Cortex 15 (9), 1332-1342.
    • Tan, H.Y., Callicott, J.H., Weinberger, D.R., 2007. Dysfunctional and compensatory prefrontal cortical systems, genes and the pathogenesis of schizophrenia. Cerebral Cortex 17 (Suppl 1), i171-181.
    • Turkheimer, F.E., Smith, C.B., Schmidt, K., 2001. Estimation of the number of "true" null hypotheses in multivariate analysis of neuroimaging data. NeuroImage 13 (5), 920-930.
    • Van Dijk, K.R., Sabuncu, M.R., Buckner, R.L., 2012. The influence of head motion on intrinsic functional connectivity MRI. NeuroImage 59, 431-438.
    • van Wijk, B.C., Stam, C.J., Daffertshofer, A., 2010. Comparing brain networks of different size and connectivity density using graph theory. PloS One 5, e13701.
    • Wang, L., Metzak, P.D., Honer, W.G., Woodward, T.S., 2010. Impaired efficiency of functional networks underlying episodic memory-for-context in schizophrenia. The Journal of neuroscience : the official journal of the Society for Neuroscience 30, 13171-13179.
    • Yung, A.R., McGorry, P.D., 1996. The prodromal phase of first-episode psychosis: past and current conceptualizations. Schizophrenia Bulletin 22, 353-370.
    • Yung, A.R., Phillips, L.J., McGorry, P.D., McFarlane, C.A., Francey, S., Harrigan, S., Patton, G.C., Jackson, H.J., 1998. Prediction of psychosis. A step towards indicated prevention of schizophrenia. The British journal of psychiatry. Supplement 172, 14-20.
    • Yung, A.R., Phillips, L.J., Yuen, H.P., Francey, S.M., McFarlane, C.A., Hallgren, M., McGorry, P.D., 2003. Psychosis prediction: 12-month follow up of a high-risk (“prodromal”) group. Schizophrenia Research 60, 21-32.
    • Zalesky, A., Fornito, A., Egan, G.F., Pantelis, C., Bullmore, E.T., 2011. The relationship between regional and inter-regional functional connectivity deficits in schizophrenia. Human Brain Mapping. http://dx.doi.org/10.1002/hbm.21379.
  • Inferred research data

    The results below are discovered through our pilot algorithms. Let us know how we are doing!

    Title Trust
    65
    65%
  • Discovered through pilot similarity algorithms. Send us your feedback.

Share - Bookmark

Cite this article