ReviewCan structure predict function in the human brain?
Introduction
The brain is composed of anatomically distinct elements interconnected by a dense web of structural links. This structural network shapes how neural dynamics—the processes underlying human cognitive function—unfold over time. Structure–function relationships are pervasive in biology and range in scale from the folding of proteins up to the biomechanics of mammalian skeletons. Structure invariably informs and constrains biological function. In what ways does structure predict function in the human brain? We review evidence at microscopic and macroscopic scales, and frame an answer from the perspectives of network theory and computational modeling.
Large-scale computational models now combine neuroanatomical and physiological connectivity data with unprecedented comprehensiveness and detail. What can these models tell us about the relationship between anatomical connectivity and dynamic interactions that develop upon the network over time?
The question gains in significance because of the accumulation of highly resolved neural connectivity data recorded from individual participants. Until the recent arrival of noninvasive diffusion imaging techniques, mapping of human brain connectivity depended largely on gross dissection or on postmortem histology. These methods left large gaps in our understanding of the structural substrate of cognition. The comprehensive description of human brain connectivity—the connectome (Sporns et al., 2005)—has now become a feasible scientific goal. The availability of detailed large-scale connectivity data offers the opportunity to understand the links between brain structure and brain function at the regional level, and parallel approaches to mapping the connectivity of single neurons will facilitate a more complete understanding of the functioning of local neural circuits.
The paper is structured as follows. In the second section we define key terms such as “structural connectivity” and “functional connectivity”, we make a distinction between two levels of brain organization, and we introduce the computational framework of network modeling approaches. The third section addresses the structure–function relationships observed among individual neurons and among small populations of neurons. We examine the evidence for precise and patterned synaptic targeting, and the potential role of such precise structure in local circuit dynamics. In the fourth section we review the evidence for a link between structure and function at the large scale. We focus on empirical studies of spontaneous and task-evoked neural interactions. We further review how structure–function relationships depend on the spatiality of the brain and how they change across time, or as a consequence of local or distributed network damage. Throughout, we attempt to establish links between empirical findings and results of network analysis and computational modeling. We close with some considerations of empirical and modeling developments in the near future.
Section snippets
Definitions, scales, and models
When asking whether “structure” determines “function” in a given context it is necessary to specify one's usage of the key terms. In the present context, we take “structure” to refer to the spatial and topological arrangement of connections between neuronal elements. The notion of “function” is more delicate. By the “function” of a particular neuron or brain region we do not refer to the set of behavioral or psychological functions (e.g. attention, memory) subserved by a given neural circuit or
Thinking inside the voxel: Structure and function of neural circuits
Ten cubic millimeters of human cerebral cortex—the approximate volume of a standard fMRI voxel—contains on the order of 105 neurons and 109 synapses (Pakkenberg and Gundersen, 1997). In human sensory cortices, such a voxel will typically contain between 10 and 40 functional domains (assuming each domain has a diameter between 300 and 600 μm). Functional domains are constituted by sets of neurons that show similar responses to variations in somatic, auditory or visual stimulation (Mountcastle,
From single voxels to the whole brain: Structure and function of large-scale systems
The analysis of spontaneous neural dynamics offers an opportunity to measure the aggregate level of relation between structural and functional connectivity in a relatively task-neutral manner. Several studies have performed a combined analysis of structural connectivity (SC) derived from diffusion imaging and tractography, and functional connectivity (FC) derived from spontaneous fluctuations of the BOLD response (reviewed in Damoiseaux and Greicius, 2009). The first such study examined SC and
Network topology of SC and FC
Network concepts have been used to define principles of the structural and functional organization of the cerebral cortex for many decades. The “mosaic organization” of the cortex into specialized regions that become functionally integrated during perception and cognition (Zeki, 1978, Zeki and Shipp, 1988), as well as the idea that large-scale connectivity in the primate brain is structurally (Felleman and Van Essen, 1991) and functionally (Mesulam, 1998) organized into multiple processing
Conclusions
Rapid advances in recording and data processing methods are beginning to yield structural and functional connection maps of brain networks at multiple scales and with unprecedented accuracy and resolution. Connectome datasets will facilitate a far clearer understanding of the relationship between structure and function in the human brain. Initial results are encouraging, in that many of the characteristics of functional brain dynamics can be traced to structural patterns in connectivity. In
Acknowledgments
The authors (CJH, JPT, OS) gratefully acknowledge support from the JS McDonnell Foundation.
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