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SUMMARY:Interareal pathways in the primate cortex - Professor Henry Kenned
 y\, Stem Cell and Brain Research Institute\, Inserm\, France
DTSTART:20131126T110000Z
DTEND:20131126T120000Z
UID:TALK49068@talks.cam.ac.uk
CONTACT:Mikail Rubinov
DESCRIPTION:Surprisingly little is known about the statistics of cortical 
 networks due to an absence of investigation at the single-cell level of th
 eir weighted and spatial properties. Using brain-wide retrograde tracing e
 xperiments in macaque we have generated a weighted and directed inter-area
 l matrix (1). This constitutes a consistent data base that reveals 36% mor
 e connections than in collated data (2). Local connectivity accounts for 8
 0% of labeled neurons\, meaning that cortex is heavily involved in local f
 unction (3). The inter-areal cortical graph has a density of 66%\, meaning
  that over two thirds of the connections that can exist\, do exist. At suc
 h densities the network is neither a sparse small world nor scale-free as 
 claimed by studies using collated data. At high graph densities binary con
 nectivity is expected to show little specificity. However\, we have shown 
 that probability of connectivity falls of with distance conferring a high-
 specificity for long-distance connections (4)\nImportantly connection weig
 hts are highly characteristic across animals\, follow a heavy-tailed logno
 rmal distribution over 6 orders of magnitude\, and decay exponentially wit
 h distance. This has enabled us to extract an exponential distance rule (E
 DR). By building random networks employing the EDR we show that there is a
  trade-off between local and global efficiency. An important finding is th
 at the EDR predicts the binary features\, the communication efficiency and
  the structural heterogeneity of the graph exhibiting a highly efficient d
 ense core as found in other information processing self-organizing network
 s eg WWW). Further\, the EDR explains the economy of connectivity\, which 
 was previously understood in terms of Small World architectures.\nIntegrat
 ion of the inter-areal network into the laminar structure of the local con
 nectivity reveals hierarchical areal relations\, which are believed to be 
 important for understanding computational processes in the cortex (5). Pre
 sently we are investigating how to combine the large-scale inter-areal net
 work with the cortical hierarchy.\n\nMarkov NT et al\, 2013\, Cereb Cortex
  DOI: 10.1093/cercor/bhs1270\nKennedy H\, Knoblauch K\, Toroczkai Z2013\, 
 NeuroImage. DOI: 10.1016/j.neuroimage.2013.1004.1031.\nMarkov NT et al\, 2
 011\, Cereb Cortex 21:1254-1272.\nMarkov NT\, Ercsey-Ravasz MM\, Lamy C\, 
 Ribeiro Gomes AR\, Magrou L\, Misery P\, Giroud P\, Barone P\, Dehay C\, T
 oroczkai Z\, Knoblauch K\, Van Essen DC\, Kennedy H\, 2013\, Proc Nat Acad
  Sci USA 110:5187-5192.\nMarkov and Kennedy\, 2013\, Curr Opin Neurobiol 2
 3:187-194.
LOCATION:MRC CBU lecture theatre\, 15 Chaucer Road
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