… in connectivity are constrained by the prior belief that there are transitions among a small
number of brain connectivity states, while connectivity … hidden Markov model that the brain is in …

… of brain connectivity and activity 11 , but precisely how spatiotemporal patterns of neural
dynamics are constrained … , structural constraints on system dynamics can be understood via the …

… If the brain network effective connectivity network estimated … test for connectivity detection
in multivariate autoregressive … effective connectivity inference using ultra-group constrained …

… brain regions, which is defined in terms of brain connectivity. … of brain connectivity, ranging
from anatomical (structural) links, to statistical (functional) and directed (effective) connections (…

… processes are distributed across the brain network. Among … Figure 1A) can be used to constrain
the MOU-EC topology in … discrete-time multivariate autoregressive (MAR) process. These …

… the STOK filter as an effective tool for modeling large-scale … model with anatomical constraints
(LSMAC) that constrains the … estimation of complex brain connectivity networks by means …

… when and where the brain network may be the most … Among other factors, our results may
also be constrained by the … underlying model is derived using multivariate autoregression (…

… information to constrain inference on directed functional … representations of whole-brain
connectivity patterns. While … Next, we aimed to study effective connectivity during the resting …

… function estimation with constrained spherical deconvolution. A … symmetric part of this
autoregressive model parameter in order … brain connectivity is predictable from anatomic network’s …

… more effectively. In order to capture the complex relationship buried in both direct and indirect
brain connections, we … It attempts to constrain the structure of the predicted SC. PCC loss is …