scholarly journals Spatial soundscape superposition, Part I: Subject motion and scene sensibility

2020 ◽  
Vol 41 (1) ◽  
pp. 288-296 ◽  
Author(s):  
William L. Martens ◽  
Michael Cohen
Keyword(s):  
Subject Motion

scholarly journals Assessing the effects of subject motion on T2relaxation under spin tagging (TRUST) cerebral oxygenation measurements using volume navigators

2017 ◽  
Vol 78 (6) ◽  
pp. 2283-2289 ◽  
Author(s):  
Jeffrey N. Stout ◽  
M. Dylan Tisdall ◽  
Patrick McDaniel ◽  
Borjan Gagoski ◽  
Divya S. Bolar ◽  
...  
Keyword(s):  
Cerebral Oxygenation ◽  
Spin Tagging ◽  
Subject Motion

Network-specific effects of age and in-scanner subject motion: A resting-state fMRI study of 238 healthy adults

NeuroImage ◽  
2012 ◽  
Vol 63 (3) ◽  
pp. 1364-1373 ◽  
Author(s):  
Athanasia M. Mowinckel ◽  
Thomas Espeseth ◽  
Lars T. Westlye
Keyword(s):  
Resting State ◽  
Resting State Fmri ◽  
Healthy Adults ◽  
Specific Effects ◽  
Fmri Study ◽  
Subject Motion

scholarly journals A novel measure of reliability in Diffusion Tensor Imaging after data rejections due to subject motion

NeuroImage ◽  
2017 ◽  
Vol 147 ◽  
pp. 57-65 ◽  
Author(s):  
Viljami Sairanen ◽  
L. Kuusela ◽  
O. Sipilä ◽  
S. Savolainen ◽  
S. Vanhatalo
Keyword(s):  
Diffusion Tensor Imaging ◽  
Diffusion Tensor ◽  
Subject Motion

scholarly journals PredPsych: A toolbox for predictive machine learning based approach in experimental psychology research

2016 ◽  
Author(s):  
Atesh Koul ◽  
Cristina Becchio ◽  
Andrea Cavallo
Keyword(s):  
Machine Learning ◽  
Experimental Psychology ◽  
Machine Learning Algorithms ◽  
Clinical Neuroscience ◽  
Data Set ◽  
Predictive Algorithms ◽  
Research Questions ◽  
User Friendly ◽  
Behavioral Markers ◽  
Subject Motion

Recent years have seen an increased interest in machine learning based predictive methods for analysing quantitative behavioural data in experimental psychology. While these methods can achieve relatively greater sensitivity compared to conventional univariate techniques, they still lack an established and accessible software framework. The goal of this work was to build an open-source toolbox – “PredPsych” – that could make these methods readily available to all psychologists. PredPsych is a user-friendly, R toolbox based on machine learning predictive algorithms. In this paper, we present the framework of PredPsych via the analysis of a recently published multiple-subject motion capture data set. In addition, we discuss examples of possible research questions that can be addressed with the machine learning algorithms implemented in PredPsych and cannot be easily investigated with mass univariate statistical analysis. We anticipate that PredPsych will be of use to researchers with limited programming experience not only in the field of psychology, but also in that of clinical neuroscience, enabling computational assessment of putative bio-behavioral markers for both prognosis and diagnosis.

scholarly journals Predicting Slice-to-Volume Transformation in Presence of Arbitrary Subject Motion

2017 ◽  
pp. 296-304 ◽  
Author(s):  
Benjamin Hou ◽  
Amir Alansary ◽  
Steven McDonagh ◽  
Alice Davidson ◽  
Mary Rutherford ◽  
...  
Keyword(s):  
Subject Motion
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