Shared Principles in Computing and Biology 2010

Brain and Computation – Shared Principles?

Olaf SpornsDepartment of Psychological and Brain Sciences

Indiana University, Bloomington, IN 47405

http://www.indiana.edu/~cortex , osporns@indiana.edu

Brain Networks

Multiple Scales – Cells, Circuits, Systems

Tamily A. Weissman (Harvard University) Patric Hagmann (EPFL/CHUV Lausanne)

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.

Brain Networks

Multiple Modes – Structural, Functional, Effective

Effective Connectivity: Network of

causal effects, combination of

functional connectivity and structural

model.

Patric Hagmann (EPFL/CHUV Lausanne) Achard et al. (2006) J. Neurosci. 26, 63 McIntosh et al. (1994) J. Neurosci. 14, 655

Networks of mammalian cerebral cortex form a small world (high clustering, short path length), and contain modules linked by hubs.

Brain Networks

Modules and Hubs Brain Networks

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.

Each functionally specialized cortical region has a unique connectional fingerprint – a unique set of inputs and outputs.

Brain Networks

Structure Shapes Function

Structural modules consist of nodes that have similar connections with other nodes.

Passingham et al. (2002) Nature Rev Neurosci 3, 606. Hilgetag et al. (2000) Phil. Trans. Royal Soc. B 355, 91

Structural modules reflect functional relationships.

regions and interconnections of

cat cerebral cortex

A BBrain Connectivity

Mapping Human Brain: Connectome and Brain Architecture

Hagmann et al. (2008) PLoS Biol. 6, e159

A significant proportion of brain activity is “intrinsic” or “spontaneous”, occurring even in the absence of explicit task or stimulus.

This intrinsic computational mode stands in contrast to standard computational models that emphasize reflexive, momentary responses.

Intrinsic Dynamics

Endogenous Neural Activity in the Human Brain

Raichle et al. (2001) PNAS 98, 676. Greicius et al. (2003) PNAS 100, 253.Fox et al. (2005) PNAS 102, 9673. Movie: Vincent, Raichle et al. (Washington University)

The Human BrainComplexity

Network Dynamics

Small-world networks promote the coexistence of functional specialization and functional integration, enabling neural dynamics of high complexity.

∑ −−=i ii

xxHHC ).()()( XXX

entropy-based measure of complexity

Kitzbichler et al. (2009) PLoS Comput Biol 5, e1000314. Petermann et al. (2009) PNAS 106, 15921.

complex neural activitysmall-world structural network

MEGPower laws in neural dynamics (human MEG, monkey MEA) suggestthat the brain exists in a critical state.

Questions:

Q1+2: Shared principles between computing and biological (neuro)sciences

Research focus on methods and approaches from complex networks

Key features of brain architecture and network topology

Importance of information integration – role of hubs?

Intrinsic versus reflexive mode of processing

The brain is a multiscale complex systems

Computation and the critical state

Serial computation – parallel networks?Serial computation – parallel networks?

Q3: Future directions

Structure-function relationships in networks

Connectomics and brain architecture – mapping of circuits and connections

Theoretical principles

Q4: Training and Resources

Interdisciplinary training programs in computational biology

Further Reading:

Graham & Rockmore (2010, in press) The packet-switching brain. J Cogn. Neurosci.

Laughlin & Sejnowski (2003) Communication in neuronal networks. Science.

Raichle (2010) Two views of brain function. Trends Cogn. Sci.

Bullmore & Sporns (2009) Complex brain networks. Nature. Rev. Neurosci.

Sporns (2010, forthcoming) Networks of the Brain. Cambridge: MIT Press.

Funded by the James S. McDonnell Foundation