NCNC FAU. Modeling the Network Architecture of the Human Brain

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1 NCNC FAU Modeling the Network Architecture of the Human Brain Olaf Sporns Department of Psychological and Brain Sciences Indiana University, Bloomington, IN osporns@indiana.edu Outline Network Science Approaches Linking Structure to Function Building a Map of the Human Brain Relating Structure to Dynamics Networks in Brain Injury and Disease Vulnerability and Lesion Modeling Examples of Complex Networks

2 Network Science Networks as Models of Complex Systems US commuting pattern A subset of the international financial network US House of Representatives committees and subcommittees Vespignani (2009) Science 325, 425. Schweitzer (2009) Science 325, 422. Porter et al. (2009) Notices of the AMS 56, Examples of Complex Networks yeast interactome human interactome Jeong et al. (2001) Nature 411, 41 Stelzl et al. (2005) Cell 122, 957

3 Multiple Scales Cells, Circuits, Systems Microscopic: Single neurons and their synaptic connections. Mesoscopic: Connections within and between microcolumns (minicolumns) or other types of local cell assemblies Macroscopic: Anatomically segregated brain regions and inter-regional pathways. Tamily A. Weissman (Harvard University) Patric Hagmann (EPFL/CHUV Lausanne) Multiple Modes Structural, Functional, Effective Anatomical (Structural) Connectivity: Pattern of structural connections between neurons, neuronal populations, or brain regions. Functional Connectivity: Pattern of statistical dependencies (e.g. temporal correlations) between distinct (often remote) neuronal elements. Effective Connectivity: Network of causal effects, combination of functional connectivity and structural model. Van Wedeen (MGH/Harvard University) Achard et al. (2006) J. Neurosci. 26, 63 McIntosh et al. (1994) J. Neurosci. 14, 655

4 Network Measures and their Interpretation Functional Segregation Functional Integration Functional Influence Measures of functional segregation: Clustering Motifs -- Modularity Measures of functional integration: Path Length -- Efficiency Measures of functional influence: Centrality Rubinov and Sporns (2010) NeuroImage Modern Network Science Research in the social sciences has focused on the structure of specific social systems and how their network structure contributes to specific functional outcomes. Research in statistical physics and complex systems has focused on identifying universal principles of network organization, on common patterns shared among very different networks e.g. small world. small world Watts & Strogatz (1998) Nature 393, 440. Tononi et al. (1998) Trends Cogn Sci 2, 474.

5 Anatomical Organization of Cerebral Cortex Principles of network architecture in cortex: Specialization Integration Streams (modules) Hierarchy Felleman and Van Essen (1991) Cerebral Cortex 1,1. Van Essen et al. (1992) Science 255, 419. Small-World Brain Networks Networks of mammalian cerebral cortex form a small world (high clustering, short path length), and contain modules linked by hubs. regions of macaque visual and sensorimotor cortex Sporns et al. (2000) Cereb Cortex 10, 127. Sporns & Zwi (2004) Neuroinformatics 2, 145. Sporns et al. (2007) PLoS ONE 2, e1049.

6 Small-World Brain Networks Each functionally specialized cortical region has a unique connectional fingerprint a unique set of inputs and outputs. Structural modules consist of nodes that have similar connections with other nodes. Structural modules reflect functional relationships. regions and interconnections of cat cerebral cortex Passingham et al. (2002) Nature Rev Neurosci 3, 606. Hilgetag et al. (2000) Phil. Trans. Royal Soc. B 355, 91 The Human Connectome The connectome can be defined on multiple scales: Microscale (neurons, synapses) Macroscale (parcellated brain regions, voxels) Mesoscale (columns, minicolumns) Most feasible in humans, with present-day technology: macroscale, diffusion imaging central aim of the NIH Human Connectome Project Other methodologies and systems: Mesoscale mapping of mouse brain connectivity (Bohland et al.) Microscale mapping of neural circuitry (Lichtman et al.) Serial EM reconstruction (Briggman and Denk) Sporns et al. (2005) PLoS Comput. Biol. 1, e42

7 Mapping Human Brain Structural Connectivity Diffusion imaging and computational tractography allow the noninvasive mapping of white matter fiber pathways. Hagmann et al. (2008) PLoS Biol. 6, e159 Mapping Human Brain Structural Connectivity Hagmann et al. (2008) PLoS Biol. 6, e159

8 A B Mapping Human Brain Structural Connectivity LH RH Hagmann et al. (2008) PLoS Biol. 6, e159 The Human Brain Mapping Human Brain Structural Connectivity Iturria-Medina et al. (2008) NeuroImage 40, Gong et al. (2009) Cereb Cortex 19, 524.

9 The Human Brain The Structural Core A Major Hub in the Brain Network analysis reveals Exponential (not scale-free) degree distribution Robust small-world attributes Multiple modules interlinked by hub regions Positive assortativity A structural core in posterior medial cortex The core is comprised of precuneus and posterior cingulate cortex, plus adjacent regions. Brain regions within the structural core share high degree, strength and betweenness centrality, and they constitute connector hubs that link all major structural modules. Hagmann et al. (2008) PLoS Biol. 6, e159 The Human Brain Modules and Hubs in the Human Brain centrality core Hagmann et al. (2008) PLoS Biol. 6, e159

10 PCC/Precuneus and Centrality Posterior Cingulate Cortex / Precuneus Converging Evidence 1 High centrality of the precuneus in structural networks (Iturrina-Medina et at., 2008; Gong et al., 2009; Hagmann et al., 2008) centrality Macaque PMC is highly connected (Parvizi et at., 2006) 2 3 PCC has high rate of resting metabolism (Gusnard and Raichle, 2001) 4 Network representation of default mode correlation strengths (Fransson and Marrelec, 2008) 1 Gong et al. (2009) Cerebral Cortex 19, Parvizi et al. (2006) PNAS 103, Gusnard & Raichle (2001) NRN 2, Fransson & Marrelec (2008) NeuroImage 42, 1178 Functional Connectivity Endogenous Neural Activity in the Human Brain A significant proportion of brain activity is intrinsic or spontaneous, occurring even in the absence of explicit task or stimulus. Spontaneous fluctuations in the fmri BOLD signal exhibit consistent anatomical patterns, with functional connectivity linking several brain regions (PCC, MPF etc) into a default mode network. Raichle et al. (2001) PNAS 98, 676. Greicius et al. (2003) PNAS 100, 253. Fox et al. (2005) PNAS 102, Movie: Vincent, Raichle et al. (Washington University)

11 Functional Connectivity Functional Networks Modularity and Hubs Resting-state functional networks have small-world topology, with a core of interconnected hub regions. Achard et al. (2006) J. Neurosci. 26, 63 Functional Connectivity Functional Networks Modularity and Hubs Network analysis of resting-state fmri signals identifies cortical hubs, and several of them are core components of the default mode network. Buckner et al. (2009) J. Neurosci. 29, 1860.

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13 Linking Structure Relating to Function Structural and Functional Connectivity Direct Comparison of Structural and Functional Connections rsfc C All Participants, All Areas r 2 = 0.62 Relation between SC and rsfc for empirical data (left) and computational model (right). Note that the fully deterministic (nonlinear and chaotic) model does not yield a simple linear SC-rsFC relationship. SC Hagmann et al. (2008) PLoS Biol. 6, e159. Honey et al. (2009) PNAS 106, Linking Structure Towards to Function a Large-Scale Model of the Human Brain Modeling Human Resting State Functional Connectivity Structural connections of the human brain predict much of the pattern seen in resting state functional connectivity. structural connectivity (SC) functional connectivity (rsfc) - empirical functional connectivity (rsfc) nonlinear model Honey et al. (2009) PNAS 106, seeds placed in PCC, MPFC

14 Networks in Brain Injury and Disease Nonlocal Lesion Effects and Disconnection The generally accepted theory according to which aphasia, agnosia, apraxia etc. are due to destruction of narrowly circumscribed appropriate praxia, gnosia, and phasia centres, must be finally discarded on the basis of more recent clinical and anatomical studies. It is just in the case of these focal symptoms that the concept of complicated dynamic disorders in the whole cortex becomes indispensable. Constantin von Monakow (1914) Lichtheim Aphasia Von Monakow (1914) Die Lokalisation im Grosshirm und der Abbau der Funktion durch Kortikale Herde Catani and Mesulam (2008) Cortex 44, 953 Networks in Brain Injury and Disease Modeling the Impact of Lesions in the Human Brain Modeled lesion locations Effect of random or targeted node deletion The structural network is vulnerable to deletion of highly central nodes, but more resilient to deletion of strong nodes, or randomly selected nodes. Alstott et al. (2009) PLoS Comput Biol (in press)

15 Networks in Brain Injury and Disease Modeling the Impact of Lesions in the Human Brain Effects of lesions in anterior cingulate (L194) or precuneus (L821) Centrality of lesion site partially predicts lesion effects Alstott et al. (2009) PLoS Comput Biol (in press) Networks in Brain Injury and Disease Network Hubs and Alzheimer s Disease Buckner et al. (2009) Identification of network hubs in resting state / task-evoked fcmri Mapping of Aβ deposition with PET imaging Buckner et al. (2009) J. Neurosci. 29, 1860

16 Networks in Brain Injury and Disease Disturbed Connectivity in Schizophrenia 1 Structural brain networks of people with schizophrenia show reduced hierarchy, longer connection distance, and abnormal hub distribution Functional connectivity at rest correlates with psychopathology Bassett et al. (2008) J. Neurosci. 28, 9239 Whitfield-Gabrieli et al. (2009) PNAS 106, 1279 Summary Summary The Brain is a Complex Network Organized on Multiple Scales Functional states are the outcome of system-wide interactions Brain Networks Form a Small World Small-world architecture allows the brain to efficiently process information, promotes complexity The Brain is Always Active Even at Rest Endogenous processes vs. exogenous perturbations, multiple time scales Human Brain Networks have Modules, Hubs and a Structural Core Core located in medial parietal cortex Hubs may serve as integrators of cortico-cortical signal traffic Individual variations clinical disturbances Computational Models Capture Large-Scale Human Brain Activity Possibility of a global brain simulator Models as tools for exploring substrates of human cognition Funded by the JS McDonnell Foundation