1,560 research outputs found
Decoupling of brain function from structure reveals regional behavioral specialization in humans
The brain is an assembly of neuronal populations interconnected by structural
pathways. Brain activity is expressed on and constrained by this substrate.
Therefore, statistical dependencies between functional signals in directly
connected areas can be expected higher. However, the degree to which brain
function is bound by the underlying wiring diagram remains a complex question
that has been only partially answered. Here, we introduce the
structural-decoupling index to quantify the coupling strength between structure
and function, and we reveal a macroscale gradient from brain regions more
strongly coupled, to regions more strongly decoupled, than expected by
realistic surrogate data. This gradient spans behavioral domains from
lower-level sensory function to high-level cognitive ones and shows for the
first time that the strength of structure-function coupling is spatially
varying in line with evidence derived from other modalities, such as functional
connectivity, gene expression, microstructural properties and temporal
hierarchy
Augmented Slepians: Bandlimited Functions that Counterbalance Energy in Selected Intervals
Slepian functions provide a solution to the optimization problem of joint
time-frequency localization. Here, this concept is extended by using a
generalized optimization criterion that favors energy concentration in one
interval while penalizing energy in another interval, leading to the
"augmented" Slepian functions. Mathematical foundations together with examples
are presented in order to illustrate the most interesting properties that these
generalized Slepian functions show. Also the relevance of this novel
energy-concentration criterion is discussed along with some of its
applications
What social face of the new EU trade agreements? Beyond the 'soft' approach
The EU has often been accused of soft approach to trade-labour linkages in trade agreement by the inclusion of labour provisions in the trade and sustainable development chapter and by a focus on cooperation and dialogue. Rather than focusing on hard enforcement proceeding, the EU is not yet exploring all the opportunities created under these chapters.
This Policy Brief outlines a different approach that the EU can use in demanding respect for labour rights in its trade agreement with third countries. It shows the need to develop a thorough, systematic and inclusive monitoring process involving civil society while developing an holistic approach for the promotion of labour rights going beyond EU’s trade relations
Guided Graph Spectral Embedding: Application to the C. elegans Connectome
Graph spectral analysis can yield meaningful embeddings of graphs by
providing insight into distributed features not directly accessible in nodal
domain. Recent efforts in graph signal processing have proposed new
decompositions-e.g., based on wavelets and Slepians-that can be applied to
filter signals defined on the graph. In this work, we take inspiration from
these constructions to define a new guided spectral embedding that combines
maximizing energy concentration with minimizing modified embedded distance for
a given importance weighting of the nodes. We show these optimization goals are
intrinsically opposite, leading to a well-defined and stable spectral
decomposition. The importance weighting allows to put the focus on particular
nodes and tune the trade-off between global and local effects. Following the
derivation of our new optimization criterion and its linear approximation, we
exemplify the methodology on the C. elegans structural connectome. The results
of our analyses confirm known observations on the nematode's neural network in
terms of functionality and importance of cells. Compared to Laplacian
embedding, the guided approach, focused on a certain class of cells (sensory,
inter- and motoneurons), provides more biological insights, such as the
distinction between somatic positions of cells, and their involvement in low or
high order processing functions.Comment: 43 pages, 7 figures, submitted to Network Neuroscienc
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