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SUMMARY:BMI SEMINAR //  Viktor Jirsa - Applications of Personalized Brain 
 Network Models in Medicine
DTSTART:20190508T121500
DTEND:20190508T131500
DTSTAMP:20260428T030200Z
UID:8d49d228500d2792017fb85fd779f19a171013f3d44950ab09474d13
CATEGORIES:Conferences - Seminars
DESCRIPTION:Viktor Jirsa\, Institut de Neurosciences des Systèmes\, Inser
 m UMR1106\, Faculté de Médecine\, Aix-Marseille Université\, Marseille\
 , France\nOver the past decade we have demonstrated that the fusion of sub
 ject-specific structural information of the human brain with mathematical 
 dynamic models allows building biologically realistic brain network models
 \, which have a predictive value\, beyond the explanatory power of each ap
 proach independently. The network nodes hold neural population models\, wh
 ich are derived using mean field techniques from statistical physics expre
 ssing ensemble activity via collective variables. Our hybrid approach fuse
 s data-driven with forward-modeling-based techniques and has been successf
 ully applied to explain healthy brain function and clinical translation in
 cluding stroke and epilepsy. Here we illustrate the workflow along the exa
 mple of epilepsy: we reconstruct personalized connectivity matrices of hum
 an epileptic patients using Diffusion Tensor weighted Imaging (DTI). Subse
 ts of brain regions generating seizures in patients with refractory partia
 l epilepsy are referred to as the epileptogenic zone (EZ). During a seizur
 e\, paroxysmal activity is not restricted to the EZ\, but may recruit othe
 r brain regions and propagate activity through large brain networks\, whic
 h comprise brain regions that are not necessarily epileptogenic. The ident
 ification of the EZ is crucial for candidates for neurosurgery and require
 s unambiguous criteria that evaluate the degree of epileptogenicity of bra
 in regions. Stability analyses of propagating waves provide a set of indic
 es quantifying the degree of epileptogenicity and predict conditions\, und
 er which seizures propagate to non-epileptogenic brain regions\, explainin
 g the responses to intracerebral electric stimulation in epileptogenic and
  non-epileptogenic areas. These results provide guidance in the presurgica
 l evaluation of epileptogenicity based on electrographic signatures in int
 racerebral electroencephalograms and have been validated in small-scale cl
 inical trials. The example of epilepsy nicely underwrites the predictive v
 alue of personalized large-scale brain network models. \n 
LOCATION:SV 1717 https://plan.epfl.ch/?room==SV%201717
STATUS:CONFIRMED
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