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Topological structures are consistently overestimated in functional complex networks.

Scientific reports
Functional complex networks have meant a pivotal change in the way we understand complex systems, being the most outstanding one the human brain. These networks have classically been reconstructed using a frequentist approach that, while simple, comp...

Representational fluidity in embodied (artificial) cognition.

Bio Systems
Theories of embodied cognition agree that the body plays some role in human cognition, but disagree on the precise nature of this role. While it is (together with the environment) fundamentally engrained in the so-called 4E (or multi-E) cognition sta...

Modeling brain dynamic state changes with adaptive mixture independent component analysis.

NeuroImage
There is a growing interest in neuroscience in assessing the continuous, endogenous, and nonstationary dynamics of brain network activity supporting the fluidity of human cognition and behavior. This non-stationarity may involve ever-changing formati...

How Concrete Do We Get Telling Stories?

Topics in cognitive science
Will reading different stories about the same event in the world result in a similar image of the world? Will reading the same story by different people result in a similar proxy for experiencing the story? The answer to both questions is no because ...

Predicting Infectious Disease Using Deep Learning and Big Data.

International journal of environmental research and public health
Infectious disease occurs when a person is infected by a pathogen from another person or an animal. It is a problem that causes harm at both individual and macro scales. The Korea Center for Disease Control (KCDC) operates a surveillance system to mi...

The Design and Mathematical Model of a Novel Variable Stiffness Extensor-Contractor Pneumatic Artificial Muscle.

Soft robotics
This article presents the design of a novel extensor-contractor pneumatic artificial muscle (ECPAM). This new actuator has numerous advantages over traditional pneumatic artificial muscles. These include the abilities to both contract and extend rela...

Generative adversarial networks for reconstructing natural images from brain activity.

NeuroImage
We explore a method for reconstructing visual stimuli from brain activity. Using large databases of natural images we trained a deep convolutional generative adversarial network capable of generating gray scale photos, similar to stimuli presented du...

Nonlinear effective connectivity measure based on adaptive Neuro Fuzzy Inference System and Granger Causality.

NeuroImage
Exploring brain networks is an essential step towards understanding functional organization of the brain, which needs characterization of linear and nonlinear connections based on measurements like EEG or MEG. Conventional measures of connectivity ar...

Referenceless distortion correction of gradient-echo echo-planar imaging under inhomogeneous magnetic fields based on a deep convolutional neural network.

Computers in biology and medicine
Single-shot gradient-echo echo-planar imaging (GE-EPI) plays a significant role in applications where high temporal resolution is necessary. However, GE-EPI is susceptible to inhomogeneous magnetic fields that will cause image distortion. Most existi...

Causal Discovery Combining K2 with Brain Storm Optimization Algorithm.

Molecules (Basel, Switzerland)
Exploring and detecting the causal relations among variables have shown huge practical values in recent years, with numerous opportunities for scientific discovery, and have been commonly seen as the core of data science. Among all possible causal di...