منابع مشابه
Multivariate pattern dependence
When we perform a cognitive task, multiple brain regions are engaged. Understanding how these regions interact is a fundamental step to uncover the neural bases of behavior. Most research on the interactions between brain regions has focused on the univariate responses in the regions. However, fine grained patterns of response encode important information, as shown by multivariate pattern analy...
متن کاملCocaine dependence and thalamic functional connectivity: a multivariate pattern analysis
Cocaine dependence is associated with deficits in cognitive control. Previous studies demonstrated that chronic cocaine use affects the activity and functional connectivity of the thalamus, a subcortical structure critical for cognitive functioning. However, the thalamus contains nuclei heterogeneous in functions, and it is not known how thalamic subregions contribute to cognitive dysfunctions ...
متن کاملMultivariate Pattern Connectivity
Whenever we engage in a cognitive task, multiple brain regions are engaged. Understanding how these regions interact is a fundamental step to uncover the neural mechanisms that make behavior possible. The majority of the investigations of interactions between brain regions have focused on the overall univariate responses in the regions. However, in the context of ‘static’ analyses, drastic adva...
متن کاملMultivariate dependence modeling using copulas
In this contribution we review models for construction of higher dimensional dependence that have arisen recent years. In particular we focus on specific generalized Farlie Gumbel (or Sarmanov) copulas which are generated by a single function (so-called generator or generator function) defined on the unit interval. An alternative approach to generalize the FGM family of copulas is to consider t...
متن کاملMultivariate Dependence beyond Shannon Information
Accurately determining dependency structure is critical to discovering a system’s causal organization. We recently showed that the transfer entropy fails in a key aspect of this—measuring information flow—due to its conflation of dyadic and polyadic relationships. We extend this observation to demonstrate that this is true of all such Shannon information measures when used to analyze multivaria...
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ژورنال
عنوان ژورنال: PLOS Computational Biology
سال: 2017
ISSN: 1553-7358
DOI: 10.1371/journal.pcbi.1005799