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Analysis of EEG data using complex geometric structurization

Authors: Eddy Kwessi, Lloyd Edwards

arXiv

Electroencephalogram (EEG) is a common tool used to understand brain activities. The data are typically obtained by placing electrodes at the surface of the scalp and recording the oscillations of cur...

mental health psychology open access

Assessing Cerebellar Disorders With Wearable Inertial Sensor Data Using Time-Frequency and Autoregressive Hidden Markov Model Approaches

Authors: Karin C. Knudson, Anoopum S. Gupta

arXiv

We use autoregressive hidden Markov models and a time-frequency approach to create meaningful quantitative descriptions of behavioral characteristics of cerebellar ataxias from wearable inertial senso...

mental health psychology open access

Cognitive factor forming an individual constituent in a driver model inferred from multiplicatory relationships between cognitive sub-factors

Authors: Firas Lethaus, Robert Kaul

arXiv

In order to reproduce human behaviour in dynamic traffic situations, a computational representation of the requisite mental processes used to carry out the complex driving tasks is required. A single...

mental health psychology open access

When words collide: Bayesian meta-analyses of distractor and target properties in the picture-word interference paradigm

Authors: Audrey Bürki, F. -Xavier Alario, Shravan Vasishth

arXiv

In the picture-word interference paradigm, participants name pictures while ignoring a written or spoken distractor word. Naming times to the pictures are slowed down by the presence of the distractor...

mental health psychology open access

Causal interpretation rules for encoding and decoding models in neuroimaging

Authors: Sebastian Weichwald, Timm Meyer, Ozan Özdenizci, Bernhard Schölkopf, Tonio Ball, Moritz Grosse-Wentrup

arXiv

Causal terminology is often introduced in the interpretation of encoding and decoding models trained on neuroimaging data. In this article, we investigate which causal statements are warranted and whi...

mental health psychology open access

Accurately Predicting Functional Connectivity from Diffusion Imaging

Authors: Cassiano O. Becker, Sergio Pequito, George J. Pappas, Michael B. Miller, Scott T. Grafton, Danielle S. Bassett, Victor M. Preciado

arXiv

Understanding the relationship between the dynamics of neural processes and the anatomical substrate of the brain is a central question in neuroscience. On the one hand, modern neuroimaging technologi...

mental health psychology open access

Nonparametric Modeling of Dynamic Functional Connectivity in fMRI Data

Authors: Søren F. V. Nielsen, Kristoffer H. Madsen, Rasmus Røge, Mikkel N. Schmidt, Morten Mørup

arXiv

Dynamic functional connectivity (FC) has in recent years become a topic of interest in the neuroimaging community. Several models and methods exist for both functional magnetic resonance imaging (fMRI...

mental health psychology open access

An integrate-and-fire model to generate spike trains with long-range dependence

Authors: Alexandre Richard, Patricio Orio, Etienne Tanré

arXiv

Long-range dependence (LRD) has been observed in a variety of phenomena in nature, and for several years also in the spiking activity of neurons. Often, this is interpreted as originating from a non-M...

mental health psychology open access

SCALPEL: Extracting Neurons from Calcium Imaging Data

Authors: Ashley Petersen, Noah Simon, Daniela Witten

arXiv

In the past few years, new technologies in the field of neuroscience have made it possible to simultaneously image activity in large populations of neurons at cellular resolution in behaving animals....

mental health psychology open access

Statistical comparison of (brain) networks

Authors: Daniel Fraiman, Ricardo Fraiman

arXiv

The study of random networks in a neuroscientific context has developed extensively over the last couple of decades. By contrast, techniques for the statistical analysis of these networks are less dev...

mental health psychology open access

A Data-Driven Approach to Extract Connectivity Structures from Diffusion Tensor Imaging Data

Authors: Yu Jin, Joseph F. JaJa, Rong Chen, Edward H. Herskovits

arXiv

Diffusion Tensor Imaging (DTI) is an effective tool for the analysis of structural brain connectivity in normal development and in a broad range of brain disorders. However efforts to derive inherent...

mental health psychology open access

From the entropy to the statistical structure of spike trains

Authors: Yun Gao, Ioannis Kontoyiannis, Elie Bienenstock

arXiv

We use statistical estimates of the entropy rate of spike train data in order to make inferences about the underlying structure of the spike train itself. We first examine a number of different para...

mental health psychology open access

The right tool for the right question --- beyond the encoding versus decoding dichotomy

Authors: Sebastian Weichwald, Moritz Grosse-Wentrup

arXiv

There are two major questions that neuroimaging studies attempt to answer: First, how are sensory stimuli represented in the brain (which we term the stimulus-based setting)? And, second, how does the...

mental health psychology open access

A new framework for Euclidean summary statistics in the neural spike train space

Authors: Sergiusz Wesolowski, Robert J. Contreras, Wei Wu

arXiv

Statistical analysis and inference on spike trains is one of the central topics in the neural coding. It is of great interest to understand the underlying structure of given neural data. Based on the...

mental health psychology open access

Effects of Scan Length and Shrinkage on Reliability of Resting-State Functional Connectivity in the Human Connectome Project

Authors: Amanda F. Mejia, Mary Beth Nebel, Anita D. Barber, Ann S. Choe, Martin A. Lindquist

arXiv

In this paper, we use data from the Human Connectome Project (N=461) to investigate the effect of scan length on reliability of resting-state functional connectivity (rsFC) estimates produced from res...

mental health psychology open access