Richard Coppola3, Daniel Weinberger4,5, Danielle S. Bassett1,6 Dynamic Brain Network Structure: Its Organization in Working Memory and Alteration in Schizophrenia Felix Siebenhühner1,2, Richard Coppola3, Daniel Weinberger4,5, Danielle S. Bassett1,6 1 Department of Physics, University of California, Santa Barbara, CA, USA 2 Neuroscience Center, University of Helsinki, Helsinki, Finnland 3 MEG Core Facility, National Institute of Mental Health, Bethesda, MD, USA 4 Genes, Cognition and Psychosis Program, Clinical Brain Disorders Branch, National Institute of Mental Health, Bethesda, MD, USA 5 Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA 6 Sage Center for the Study of the Mind, University of California, Santa Barbara, CA, USA October 14, 2012

Oscillatory Brain Networks Human brain processes information over a network of synchronous oscillatory activity

Oscillatory Brain Networks Human brain processes information over a network of synchronous oscillatory activity Changes occur on: Short time scales (during task, mind-wandering) Long time scales (in development, learning, training, but also disease)

Oscillatory Brain Networks Abnormal patterns in schizophrenia (SZ) → 'Dysconnectivity hypothesis' (Volkow 1988, Friston 1998)

Oscillatory Brain Networks Abnormal patterns in schizophrenia (SZ) → 'Dysconnectivity hypothesis' (Volkow 1988, Friston 1998) Very common in SZ are impairments of exec. functions, working memory (Haenschel 2011)

Oscillatory Brain Networks Abnormal patterns in schizophrenia (SZ) → 'Dysconnectivity hypothesis' (Volkow 1988, Friston 1998) Very common in SZ are impairments of exec. functions, working memory (Haenschel 2011) Cross-frequency interaction vital to these functions (Sauseng 2008, Axmacher 2010)

Oscillatory Brain Networks Abnormal patterns in schizophrenia (SZ) → 'Dysconnectivity hypothesis' (Volkow 1988, Friston 1998) Very common in SZ are impairments of exec. functions, working memory (Haenschel 2011) Cross-frequency interaction vital to these functions (Sauseng 2008, Axmacher 2010) Changes associated with genetic risk factors

Oscillatory Brain Networks Abnormal patterns in schizophrenia (SZ) → 'Dysconnectivity hypothesis' (Volkow 1988, Friston 1998) Very common in SZ are impairments of exec. functions, working memory (Haenschel 2011) Cross-frequency interaction vital to these functions (Sauseng 2008, Axmacher 2010) Changes associated with genetic risk factors → Useful as diagnostic biomarkers?

Previous Work Earlier study (Bassett 2009): Cost-efficiency (CE) of network organization lower in people with SZ than in healthy subjects Task performance (working memory task) correlated with CE in both groups

Data Analysis 14 people with schizophrenia & 14 healthy controls (matched for age and gender) MEG Data recorded at NIMH during 2-back visual working memory task 66 time windows per subject (~1.8s) Analysis of γ, β, α and θ bands and cross- frequency networks

Construction of Oscillatory Networks

Transformation to Binary Networks We obtain binary matrices by thresholding to retain only the n% strongest connections Here we analyze the density/cost range from n=1% to 50% in steps of 1%

Functional Data Analysis (FDA) Novel statistical technique (Ramsay 2005) Calculation of the pairwise areas between two sets of curves, comparison with permutation test (n=20000) Here: Network diagnostics as a function of network density HC SZ HC SZ

Results of FDA for Network Diagnostics

Dynamic Changes in Brain Networks

Dynamic Changes in Brain Networks Coefficient of Variation as measure of temporal variability → Higher in people with schizophrenia for most network diagnostics

Discussion and Outlook Further support for dysconnectivity hypothesis in schizophrenia

Discussion and Outlook Further support for dysconnectivity hypothesis in schizophrenia Dynamics of networks also appear to be altered

Discussion and Outlook Further support for dysconnectivity hypothesis in schizophrenia Dynamics of networks also appear to be altered Indication that cross-frequency interaction is important for WM, altered in SZ

Discussion and Outlook Further support for dysconnectivity hypothesis in schizophrenia Dynamics of networks also appear to be altered Indication that cross-frequency interaction is important for WM, altered in SZ → Network properties as intermediate phenotypes, diagnostic biomarkers?

Discussion and Outlook Further support for dysconnectivity hypothesis in schizophrenia Dynamics of networks also appear to be altered Indication that cross-frequency interaction is important for WM, altered in SZ → Network properties as intermediate phenotypes, diagnostic biomarkers? For a better understanding of schizophrenia, further studies are necessary:

Discussion and Outlook Further support for dysconnectivity hypothesis in schizophrenia Dynamics of networks also appear to be altered Indication that cross-frequency interaction is important for WM, altered in SZ → Network properties as intermediate phenotypes, diagnostic biomarkers? For a better understanding of schizophrenia, further studies are necessary: Inclusion of healthy siblings of SZ patients Multimodal imaging studies Theoretical work and modelling

References Correspondence: felix.siebenhuhner@helsinki.fi Volkow et. al., 1988: Brain interactions in chronic schizophrenics under resting and activation conditions. Schizophr. Res. 1, 47 Friston, K.J., 1998: The disconnection hypothesis. Schizophr. Res. 30 (2), 115–125. Ramsay, J.O. and Silverman, B.W., 2005: Functional Data Analysis. Springer Haenschel, C and Linden, D., 2011: Exploring intermediate phenotypes with EEG: Working memory dysfunction in schizophrenia. Behavioural Brain Research 216 (2011) 481–495 P. Sauseng,W. Klimesch,W. R. Gruber, and N. Birbaumer, 2008, Cross-frequency phase synchronization: a brain mechanism of memory matching and attention. NeuroImage, vol. 40, no. 1, pp. 308–17, 2008. Axmacher N., Henseler M. M., Jensen O., Weinreich I., Elger C. E., Fell J., 2010, Cross-frequency coupling supports multi-item working memory in the human hippocampus. Proc. Natl. Acad. Sci. U.S.A. 107, 3228–3233 Bassett, D.S., Meyer-Lindenberg, A., Weinberger, D.R., Coppola, R., Bullmore, E., 2009, Cognitive fitness of cost-efficient brain functional networks, Proc. Natl. Acad. Sci. U.S.A. 106 (28), 11747–11752. Bassett, D.S., et al., Altered resting state complexity in schizophrenia, NeuroImage (2011), doi:10.1016/j.neuroimage.2011.10.002 Correspondence: felix.siebenhuhner@helsinki.fi