Authors: Claire Donnat, Leonardo Tozzi, Susan Holmes
arXiv
Brain connectomics is a developing field in neurosciences which strives to understand cognitive processes and psychiatric diseases through the analysis of interactions between brain regions. However,...
Authors: Pietro Verzelli, Laura Sacerdote
arXiv
Simultaneous recordings from many neurons hide important information and the connections characterizing the network remain generally undiscovered despite the progresses of statistical and machine lear...
Authors: M. Dashti Moghaddam, Jiong Liu, John G. Holden, R. A. Serota
arXiv
We use Generalized Beta Prime distribution, also known as GB2, for fitting response time distributions. This distribution, characterized by one scale and three shape parameters, is incredibly flexible...
Authors: Balazs Szalkai, Vince K. Grolmusz, Vince I. Grolmusz, Coalition Against Major Diseases
arXiv
Background: The concept of combinatorial biomarkers was conceived around 2010: it was noticed that simple biomarkers are often inadequate for recognizing and characterizing complex diseases. Methods...
Authors: Carsten Allefeld, John-Dylan Haynes
arXiv
Multi-voxel pattern analysis (MVPA) is a fruitful and increasingly popular complement to traditional univariate methods of analyzing neuroimaging data. We propose to replace the standard 'decoding' ap...
Authors: Seungyong Hwang, Thomas C. M. Lee, Debashis Paul, Jie Peng
arXiv
Due to recent technological advances, large brain imaging data sets can now be collected. Such data are highly complex so extraction of meaningful information from them remains challenging. Thus, ther...
Authors: Krempl, Georg, Kottke, Daniel, Pham Minh, Tuan
arXiv
Analysing correlations between streams of events is an important problem. It arises for example in Neurosciences, when the connectivity of neurons should be inferred from spike trains that record neur...
Authors: Matheus B. Guerrero, Raphaël Huser, Hernando Ombao
arXiv
Epilepsy is a chronic neurological disorder affecting more than 50 million people globally. An epileptic seizure acts like a temporary shock to the neuronal system, disrupting normal electrical activi...
Authors: Alex H. Williams, Scott W. Linderman
arXiv
Individual neurons often produce highly variable responses over nominally identical trials, reflecting a mixture of intrinsic "noise" and systematic changes in the animal's cognitive and behavioral st...
Authors: Chee-Ming Ting, Jeremy I. Skipper, Steven L. Small, Hernando Ombao
arXiv
We consider the challenges in extracting stimulus-related neural dynamics from other intrinsic processes and noise in naturalistic functional magnetic resonance imaging (fMRI). Most studies rely on in...
Authors: Nathan Tung, Jerome Sanes, Eli Upfal, Ani Eloyan
arXiv
Functional connectivity (FC) refers to the investigation of interactions between brain regions to understand integration of neural activity in several regions. FC is often estimated using functional m...
Authors: A. V. Paraskevov, A. S. Minkin
arXiv
There are numerous examples of natural and artificial processes that represent stochastic sequences of events followed by an absolute refractory period during which the occurrence of a subsequent even...
Authors: Jan Sosulski, David Hübner, Aaron Klein, Michael Tangermann
arXiv
The decoding of brain signals recorded via, e.g., an electroencephalogram, using machine learning is key to brain-computer interfaces (BCIs). Stimulation parameters or other experimental settings of t...
Authors: Rahul Biswas, Eli Shlizerman
arXiv
The representation of the flow of information between neurons in the brain based on their activity is termed the causal functional connectome. Such representation incorporates the dynamic nature of ne...
Authors: Danilo Bzdok, John Ioannidis
arXiv
The last decades saw dramatic progress in brain research. These advances were often buttressed by probing single variables to make circumscribed discoveries, typically through null hypothesis signific...