TY - JOUR
T1 - Inference of direct and multistep effective connectivities from functional connectivity of the brain and of relationships to cortical geometry
AU - Mehta-Pandejee, Grishma
AU - Robinson, Peter Alexander
AU - Henderson, James A.
AU - Aquino, K. M.
AU - Sarkar, Somwrita
PY - 2017/5/1
Y1 - 2017/5/1
N2 - Background The problem of inferring effective brain connectivity from functional connectivity is under active investigation, and connectivity via multistep paths is poorly understood. New method A method is presented to calculate the direct effective connection matrix (deCM), which embodies direct connection strengths between brain regions, from functional CMs (fCMs) by minimizing the difference between an experimental fCM and one calculated via neural field theory from an ansatz deCM based on an experimental anatomical CM. Results The best match between fCMs occurs close to a critical point, consistent with independent published stability estimates. Residual mismatch between fCMs is identified to be largely due to interhemispheric connections that are poorly estimated in an initial ansatz deCM due to experimental limitations; improved ansatzes substantially reduce the mismatch and enable interhemispheric connections to be estimated. Various levels of significant multistep connections are then imaged via the neural field theory (NFT) result that these correspond to powers of the deCM; these are shown to be predictable from geometric distances between regions. Comparison with existing methods This method gives insight into direct and multistep effective connectivity from fCMs and relating to physiology and brain geometry. This contrasts with other methods, which progressively adjust connections without an overarching physiologically based framework to deal with multistep or poorly estimated connections. Conclusions deCMs can be usefully estimated using this method and the results enable multistep connections to be investigated systematically.
AB - Background The problem of inferring effective brain connectivity from functional connectivity is under active investigation, and connectivity via multistep paths is poorly understood. New method A method is presented to calculate the direct effective connection matrix (deCM), which embodies direct connection strengths between brain regions, from functional CMs (fCMs) by minimizing the difference between an experimental fCM and one calculated via neural field theory from an ansatz deCM based on an experimental anatomical CM. Results The best match between fCMs occurs close to a critical point, consistent with independent published stability estimates. Residual mismatch between fCMs is identified to be largely due to interhemispheric connections that are poorly estimated in an initial ansatz deCM due to experimental limitations; improved ansatzes substantially reduce the mismatch and enable interhemispheric connections to be estimated. Various levels of significant multistep connections are then imaged via the neural field theory (NFT) result that these correspond to powers of the deCM; these are shown to be predictable from geometric distances between regions. Comparison with existing methods This method gives insight into direct and multistep effective connectivity from fCMs and relating to physiology and brain geometry. This contrasts with other methods, which progressively adjust connections without an overarching physiologically based framework to deal with multistep or poorly estimated connections. Conclusions deCMs can be usefully estimated using this method and the results enable multistep connections to be investigated systematically.
KW - Anatomical connectivity
KW - Cortical geometry
KW - Effective connectivity
KW - Functional connectivity
KW - Global mode removal
KW - Multistep connections
KW - Neural field theory
KW - Norm-minimization
UR - http://www.scopus.com/inward/record.url?scp=85016447722&partnerID=8YFLogxK
U2 - 10.1016/j.jneumeth.2017.03.014
DO - 10.1016/j.jneumeth.2017.03.014
M3 - Article
C2 - 28342831
AN - SCOPUS:85016447722
SN - 0165-0270
VL - 283
SP - 42
EP - 54
JO - Journal of Neuroscience Methods
JF - Journal of Neuroscience Methods
ER -