@article{ansado_how_2021,

title = {How brain imaging provides predictive biomarkers for therapeutic success in the context of virtual reality cognitive training},

author = {J. Ansado and C. Chasen and S. Bouchard and G. Northoff},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089070480&doi=10.1016%2fj.neubiorev.2020.05.018&partnerID=40&md5=8e5ea676958e050b32a893830dbc2a93},

doi = {10.1016/j.neubiorev.2020.05.018},

issn = {01497634},

year  = {2021},

date = {2021-01-01},

journal = {Neuroscience and Biobehavioral Reviews},

volume = {120},

pages = {583–594},

abstract = {As Virtual reality (VR) is increasingly used in neurological disorders such as stroke, traumatic brain injury, or attention deficit disorder, the question of how it impacts the brain's neuronal activity and function becomes essential. VR can be combined with neuroimaging to offer invaluable insight into how the targeted brain areas respond to stimulation during neurorehabilitation training. That, in turn, could eventually serve as a predictive marker for therapeutic success. Functional magnetic resonance imaging (fMRI) identified neuronal activity related to blood flow to reveal with a high spatial resolution how activation patterns change, and restructuring occurs after VR training. Portable and quiet, electroencephalography (EEG) conveniently allows the clinician to track spontaneous electrical brain activity in high temporal resolution. Then, functional near-infrared spectroscopy (fNIRS) combines the spatial precision level of fMRIs with the portability and high temporal resolution of EEG to constitute an ideal measuring tool in virtual environments (VEs). This narrative review explores the role of VR and concurrent neuroimaging in cognitive rehabilitation. © 2020 Elsevier Ltd},

note = {Publisher: Elsevier Ltd},

keywords = {accuracy, attention deficit disorder, biological monitoring, brain depth stimulation, brain electrophysiology, brain radiography, brain region, cell function, cerebrovascular accident, clinician, cognition, Cognitive rehabilitation, disease marker, electroencephalogram, Electroencephalography, functional magnetic resonance imaging, functional near-infrared spectroscopy, human, image quality, in vivo study, nerve cell, neuroimaging, neurologic disease, neuropsychological test, neuropsychology, neurorehabilitation, nonhuman, prediction, priority journal, review, therapy effect, training, traumatic brain injury, virtual reality, virtual reality cognitive training},

pubstate = {published},

tppubtype = {article}

}

@article{royer_efficient_2016,

title = {Efficient visual information for unfamiliar face matching despite viewpoint variations: It's not in the eyes!},

author = {J. Royer and C. Blais and V. Barnabé-Lortie and M. Carré and J. Leclerc and D. Fiset},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84968779426&doi=10.1016%2fj.visres.2016.04.004&partnerID=40&md5=4c63f6eea279f7322c9af23ae9ed22c1},

doi = {10.1016/j.visres.2016.04.004},

issn = {00426989 (ISSN)},

year  = {2016},

date = {2016-01-01},

journal = {Vision Research},

volume = {123},

pages = {33–40},

abstract = {Faces are encountered in highly diverse angles in real-world settings. Despite this considerable diversity, most individuals are able to easily recognize familiar faces. The vast majority of studies in the field of face recognition have nonetheless focused almost exclusively on frontal views of faces. Indeed, a number of authors have investigated the diagnostic facial features for the recognition of frontal views of faces previously encoded in this same view. However, the nature of the information useful for identity matching when the encoded face and test face differ in viewing angle remains mostly unexplored. The present study addresses this issue using individual differences and bubbles, a method that pinpoints the facial features effectively used in a visual categorization task. Our results indicate that the use of features located in the center of the face, the lower left portion of the nose area and the center of the mouth, are significantly associated with individual efficiency to generalize a face's identity across different viewpoints. However, as faces become more familiar, the reliance on this area decreases, while the diagnosticity of the eye region increases. This suggests that a certain distinction can be made between the visual mechanisms subtending viewpoint invariance and face recognition in the case of unfamiliar face identification. Our results further support the idea that the eye area may only come into play when the face stimulus is particularly familiar to the observer. © 2016 Elsevier Ltd.},

note = {Publisher: Elsevier Ltd},

keywords = {accuracy, adult, article, association, attention, Bubbles, Evoked Potentials, eye fixation, Face, face profile, face recognition, Facial Recognition, facies, female, Fixation, human, human experiment, Humans, Image analysis, Individual differences, male, Ocular, Pattern Recognition, Photic Stimulation, photostimulation, physiology, priority journal, procedures, Psychophysics, recognition, Recognition (Psychology), regression analysis, task performance, unfamiliar face matching, viewpoint variation, Viewpoint variations, Visual, visual discrimination, visual evoked potential, visual information, visual memory, visual stimulation, visual system parameters, Young Adult},

pubstate = {published},

tppubtype = {article}

}

@article{allili_likelihood-based_2015,

title = {Likelihood-based feature relevance for figure-ground segmentation in images and videos},

author = {M. S. Allili and D. Ziou},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84952631642&doi=10.1016%2fj.neucom.2015.04.015&partnerID=40&md5=833948d0784e0dc42c2245b9343971dd},

doi = {10.1016/j.neucom.2015.04.015},

issn = {09252312},

year  = {2015},

date = {2015-01-01},

journal = {Neurocomputing},

volume = {167},

pages = {658–670},

abstract = {We propose an efficient method for image/video figure-ground segmentation using feature relevance (FR) and active contours. Given a set of positive and negative examples of a specific foreground (an object of interest (OOI) in an image or a tracked objet in a video), we first learn the foreground distribution model and its characteristic features that best discriminate it from its contextual background. For this goal, an objective function based on feature likelihood ratio is proposed for supervised FR computation. FR is then incorporated in foreground segmentation of new images and videos using level sets and energy minimization. We show the effectiveness of our approach on several examples of image/video figure-ground segmentation. © 2015 Elsevier B.V.},

note = {Publisher: Elsevier},

keywords = {accuracy, algorithm, article, calculation, Feature relevance, Figure-ground segmentations, Gaussian mixture model (GMMs), Image analysis, Image Enhancement, image quality, Image segmentation, Level Set, linear system, mathematical analysis, mathematical model, Negative examples, priority journal, Video cameras, videorecording},

pubstate = {published},

tppubtype = {article}

}

@article{renaud_stress_1997,

title = {The stress of stroop performance: Physiological and emotional responses to color-word interference, task pacing, and pacing speed},

author = {P. Renaud and J. -P. Blondin},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-0030754719&doi=10.1016%2fS0167-8760%2897%2900049-4&partnerID=40&md5=79992021abdbf3ef544e20b2a11f29ff},

doi = {10.1016/S0167-8760(97)00049-4},

issn = {01678760},

year  = {1997},

date = {1997-01-01},

journal = {International Journal of Psychophysiology},

volume = {27},

number = {2},

pages = {87–97},

abstract = {Heart rate, frequency of skin conductance responses, and self-reported anxiety were measured during performance of a computer version of the Stroop Color-Word Interference Test, and during a non-conflicting control task involving the color naming of color patches. Stroop and control stimuli were presented individually in order to vary task pacing. Subjects (N = 48) were divided into three groups assigned to self-paced, externally-paced, and fast externally-paced conditions. Performance data revealed that the relative proportion of speed and accuracy reductions which resulted from the Stroop interference varied according to task pacing and pacing speed. Stroop performance was accompanied by heightened HR levels which were sustained throughout the series. State-Anxiety scores increased after both tasks, but only among subjects who completed a large number of trials, i.e. subjects in the self-paced and fast externally-paced groups. Skin conductance responses only varied according to task order and time within series, irrespective of Stroop interference or task pacing. Overall, the results remained in accordance with an effort account of the relationship between attention and cardiac activity. They also provided indications on how the Stroop test may act as an efficient laboratory stressor.},

keywords = {accuracy, Adolescent, adult, Anxiety, article, attention, Color, controlled study, emotion, Emotions, Galvanic Skin Response, Heart Rate, human, human experiment, Humans, male, mental stress, mental test, normal human, Psychological Tests, Psychomotor Performance, self report, skin conductance, task performance},

pubstate = {published},

tppubtype = {article}

}