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SUMMARY:Human brain networks from functional MRI - Professor Ed Bullmore\,
  Head of Dept Psychiatry\, Cambridge
DTSTART:20160114T153000Z
DTEND:20160114T163000Z
UID:TALK63601@talks.cam.ac.uk
CONTACT:Deborah McSkimming
DESCRIPTION:Functional MRI has many significant disadvantages as a source 
 of information about nervous systems. It does not directly represent neuro
 nal activity\; it has coarse spatial and temporal resolution compared to t
 he range of scales of space and time that brains subtend\; it is not measu
 red in SI units\; experimental recordings are at least 80% noise\; etc. No
 netheless\, the patterns of between-regional correlation in slowly oscilla
 ting fMRI time series have turned out to be robustly replicable and not tr
 ivially explained. Graph theoretical models of human fMRI networks\, deriv
 ed from association matrices of pair-wise functional connectivity estimate
 d for all possible pairs of 300 regional nodes\, demonstrate complex topol
 ogy: small-worldness\, hubs\, modules\, core/periphery\, etc. These featur
 es are replicable and heritable. The topological and spatial or geometrica
 l organization of fMRI networks is consistent with the theory that their f
 ormation is largely determined by the trade-off between a few competitive 
 factors or conservation laws. Hypothetically\, an economic trade-off betwe
 en the biological cost and the topological value of network components cou
 ld drive the formation of fMRI networks. To test the generality of this an
 d other hypotheses generated by connectomic analysis of “resting state
 ” fMRI data\, graph theoretical methods can be used to make comparable m
 easurements in many other neuroscientific datasets. Meta-analysis of large
  scale libraries (N 1000 primary papers) of fMRI activation studies demons
 trated that more expensive topological features (hubs\, rich club) were as
 sociated with domain-general\, “higher-order” cognitive functions\; an
 d that high cost / high value network hubs were hotspots for structural br
 ain deficits associated with many different brain disorders (including Alz
 heimer’s disease and schizophrenia). Many of the complex topological cha
 racteristics of large-scale human fMRI networks are qualitatively reproduc
 ed at the microscopic scale of functional networks derived from multi-elec
 trode array recordings of growing neuronal cultures in vitro. The economic
 al model of a trade-off between biological cost and topological value has 
 been specifically re-affirmed by analysis of viral tract tracing data (~40
 0 anterograde tracer injection experiments) on the anatomical connectivity
  of the mouse brain. We conclude that despite the well-known limitations o
 f fMRI\, it has emerged as almost uniquely capable of measuring the comple
 x network organization of human brain function in a way that is physically
 \, neurobiologically\, cognitively\, and clinically meaningful.
LOCATION:Lecture Theatre\, MRC Cognition and Brain Sciences Unit\, Chaucer
  Road
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