Slide
Centre Interdisciplinaire
de Recherche et d’Innovation
en Cybersécurité et Société
de Recherche et d’Innovation
en Cybersécurité et Société
1.
Côté, S. S. -P.; Brideau-Duquette, M.; Lafortune, D.; Pfaus, J. G.; Renaud, P.
Dans: O., Poquet; A., Ortega-Arranz; O., Viberg; I.-A., Chounta; B., McLaren; J., Jovanovic (Ed.): International Conference on Computer Supported Education, CSEDU - Proceedings, p. 694–700, Science and Technology Publications, Lda, 2024, ISBN: 21845026 (ISSN); 978-989758697-2 (ISBN), (Journal Abbreviation: International Conference on Computer Supported Education, CSEDU - Proceedings).
Résumé | Liens | BibTeX | Étiquettes: Affordances, Behavioral measures, Computer vision, E-learning, Electroencephalography, Electrophysiology, Gaze Behaviour, Gaze behaviours, Immersive, Learning, Physiological measures, Quantitative electroencephalography, Quantitative Electroencephalography (qEEG), Sexual Presence, Therapeutic Application, Vaginal Photoplethysmography, virtual reality
@inproceedings{cote_investigating_2024,
title = {Investigating Female Sexual Presence Through Triangulation of Behavioral and Physiological Measures in Virtual Reality: Towards Therapeutic Applications for Sexual Disorders},
author = {S. S. -P. Côté and M. Brideau-Duquette and D. Lafortune and J. G. Pfaus and P. Renaud},
editor = {Poquet O. and Ortega-Arranz A. and Viberg O. and Chounta I.-A. and McLaren B. and Jovanovic J.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85193914916&doi=10.5220%2f0012754700003693&partnerID=40&md5=435ba537cddf1277ed1b459b8a0b1984},
doi = {10.5220/0012754700003693},
isbn = {21845026 (ISSN); 978-989758697-2 (ISBN)},
year = {2024},
date = {2024-01-01},
booktitle = {International Conference on Computer Supported Education, CSEDU - Proceedings},
volume = {1},
pages = {694–700},
publisher = {Science and Technology Publications, Lda},
abstract = {Exposure to sexual contexts by means of immersive, extended reality technologies, offer an opportunity to both: better understand sexual responding, and in turn, offers insights as to how the same technology could help in treating sexual disorders. The present papers reports on the ability of behavioural (i.e., oculometry) and physiological (i.e., electroencephalography and vaginal plethysmography) to conjointly predict subjective sexual feelings (i.e., subjective sexual presence), this, using a sample of 12 heterosexual cisgendered women. Measurements pertained to the participants living a sexual immersion (via a virtual reality headset) with an opposite sex virtual character engaging in sexually suggestive behaviour. Results suggest that all the tested behavioural and physiological measurements could play a role in the shaping of sexual presence. Results are discussed with therapeutic learning processes considerations in mind. Copyright © 2024 by SCITEPRESS – Science and Technology Publications, Lda.},
note = {Journal Abbreviation: International Conference on Computer Supported Education, CSEDU - Proceedings},
keywords = {Affordances, Behavioral measures, Computer vision, E-learning, Electroencephalography, Electrophysiology, Gaze Behaviour, Gaze behaviours, Immersive, Learning, Physiological measures, Quantitative electroencephalography, Quantitative Electroencephalography (qEEG), Sexual Presence, Therapeutic Application, Vaginal Photoplethysmography, virtual reality},
pubstate = {published},
tppubtype = {inproceedings}
}
Exposure to sexual contexts by means of immersive, extended reality technologies, offer an opportunity to both: better understand sexual responding, and in turn, offers insights as to how the same technology could help in treating sexual disorders. The present papers reports on the ability of behavioural (i.e., oculometry) and physiological (i.e., electroencephalography and vaginal plethysmography) to conjointly predict subjective sexual feelings (i.e., subjective sexual presence), this, using a sample of 12 heterosexual cisgendered women. Measurements pertained to the participants living a sexual immersion (via a virtual reality headset) with an opposite sex virtual character engaging in sexually suggestive behaviour. Results suggest that all the tested behavioural and physiological measurements could play a role in the shaping of sexual presence. Results are discussed with therapeutic learning processes considerations in mind. Copyright © 2024 by SCITEPRESS – Science and Technology Publications, Lda.
2.
Côté, S. S. -P.; Brideau-Duquette, M.; Labbé, D.; Renaud, P.
Sexual Presence in Virtual Reality: A qEEG Exploration Article d'actes
Dans: Proc. - IEEE Conf. Virtual Real. 3D User Interfaces Abstr. Workshops, VRW, p. 947–948, Institute of Electrical and Electronics Engineers Inc., 2024, ISBN: 979-835037449-0 (ISBN), (Journal Abbreviation: Proc. - IEEE Conf. Virtual Real. 3D User Interfaces Abstr. Workshops, VRW).
Résumé | Liens | BibTeX | Étiquettes: Electroencephalography, Electrophysiology, Exposed to, Immersive technologies, Quantitative electroencephalography, Sexual Presence, Virtual character, virtual reality, Virtual scenario
@inproceedings{cote_sexual_2024,
title = {Sexual Presence in Virtual Reality: A qEEG Exploration},
author = {S. S. -P. Côté and M. Brideau-Duquette and D. Labbé and P. Renaud},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195564684&doi=10.1109%2fVRW62533.2024.00270&partnerID=40&md5=3b0e533b4b5ab49d00103d5e71792d26},
doi = {10.1109/VRW62533.2024.00270},
isbn = {979-835037449-0 (ISBN)},
year = {2024},
date = {2024-01-01},
booktitle = {Proc. - IEEE Conf. Virtual Real. 3D User Interfaces Abstr. Workshops, VRW},
pages = {947–948},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {The increasing use of immersive technologies for sexual purposes raises questions about their capacity to enhance a unique aspect of presence-Sexual Presence (SP). Investigating this phenomenon hinges on our ability to measure it accurately. This paper improves our understanding of SP by identifying potential quantitative electroencephalography variables associated with SP. Twelve heterosexual cisgender males were exposed to virtual scenarios featuring sexual content performed by a Virtual Character (VC). After viewing, participants completed a Sexual Presence questionnaire. Correlations were observed between self-reported SP and the alpha band activity in the frontal and parietal regions. © 2024 IEEE.},
note = {Journal Abbreviation: Proc. - IEEE Conf. Virtual Real. 3D User Interfaces Abstr. Workshops, VRW},
keywords = {Electroencephalography, Electrophysiology, Exposed to, Immersive technologies, Quantitative electroencephalography, Sexual Presence, Virtual character, virtual reality, Virtual scenario},
pubstate = {published},
tppubtype = {inproceedings}
}
The increasing use of immersive technologies for sexual purposes raises questions about their capacity to enhance a unique aspect of presence-Sexual Presence (SP). Investigating this phenomenon hinges on our ability to measure it accurately. This paper improves our understanding of SP by identifying potential quantitative electroencephalography variables associated with SP. Twelve heterosexual cisgender males were exposed to virtual scenarios featuring sexual content performed by a Virtual Character (VC). After viewing, participants completed a Sexual Presence questionnaire. Correlations were observed between self-reported SP and the alpha band activity in the frontal and parietal regions. © 2024 IEEE.
3.
Léveillé, E.; Desjardins, M.; Dumel, G.; Blais, C.; Saint-Amour, D.; Scherzer, P.; Beaumont, L. De
Effects of Emotion and Emotional Ambiguity on Early Visual Event-Related Potentials Article de journal
Dans: Emotion, vol. 23, no 3, p. 787–804, 2022, ISSN: 15283542 (ISSN), (Publisher: American Psychological Association).
Résumé | Liens | BibTeX | Étiquettes: adult, article, Brain, clinical article, controlled study, Electroencephalography, electroencephalography (EEG), emotion, emotional facial expression (EFE), event related potential, event-related potential (ERP), Facial Expression, female, human, human experiment, male, mass univariate statistics, photography, univariate analysis
@article{leveille_effects_2022,
title = {Effects of Emotion and Emotional Ambiguity on Early Visual Event-Related Potentials},
author = {E. Léveillé and M. Desjardins and G. Dumel and C. Blais and D. Saint-Amour and P. Scherzer and L. De Beaumont},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135853427&doi=10.1037%2femo0001119&partnerID=40&md5=7e89d6dee0b96766b8a359a3a9be4d73},
doi = {10.1037/emo0001119},
issn = {15283542 (ISSN)},
year = {2022},
date = {2022-01-01},
journal = {Emotion},
volume = {23},
number = {3},
pages = {787–804},
abstract = {The modulation of early sensory event-related potentials such as the P1, N1, and N170 by emotion and emotional ambiguity is still controversial. Some studies have found a modulation of one or all of these components by one or both of these factors, whereas others have failed to show such results. The objective of this study was to investigate the effects of emotion and ambiguity on the behavioral and electrophysiological responses to a morphed emotion recognition task. Thirty-seven healthy participants (19 men) completed an emotion recognition task where photographs of a male face expressing the six basic emotions morphed with another emotion (in a proportion ranging from 26% to 74%) were randomly presented while electroencephalography was recorded. After each face presentation, participants were asked to identify the facial emotion. We found an emotional effect on the P1, N1, and N170, with greater amplitudes for some emotional facial expressions than for others. However, we found no significant emotional ambiguity effect or interaction between emotion and ambiguity for any of these components. These findings suggest that computation of emotional facial expressions (regardless of their ambiguity) occurs from the early stages of brain processing. © 2022 American Psychological Association},
note = {Publisher: American Psychological Association},
keywords = {adult, article, Brain, clinical article, controlled study, Electroencephalography, electroencephalography (EEG), emotion, emotional facial expression (EFE), event related potential, event-related potential (ERP), Facial Expression, female, human, human experiment, male, mass univariate statistics, photography, univariate analysis},
pubstate = {published},
tppubtype = {article}
}
The modulation of early sensory event-related potentials such as the P1, N1, and N170 by emotion and emotional ambiguity is still controversial. Some studies have found a modulation of one or all of these components by one or both of these factors, whereas others have failed to show such results. The objective of this study was to investigate the effects of emotion and ambiguity on the behavioral and electrophysiological responses to a morphed emotion recognition task. Thirty-seven healthy participants (19 men) completed an emotion recognition task where photographs of a male face expressing the six basic emotions morphed with another emotion (in a proportion ranging from 26% to 74%) were randomly presented while electroencephalography was recorded. After each face presentation, participants were asked to identify the facial emotion. We found an emotional effect on the P1, N1, and N170, with greater amplitudes for some emotional facial expressions than for others. However, we found no significant emotional ambiguity effect or interaction between emotion and ambiguity for any of these components. These findings suggest that computation of emotional facial expressions (regardless of their ambiguity) occurs from the early stages of brain processing. © 2022 American Psychological Association
4.
Ansado, J.; Chasen, C.; Bouchard, S.; Northoff, G.
How brain imaging provides predictive biomarkers for therapeutic success in the context of virtual reality cognitive training Article de journal
Dans: Neuroscience and Biobehavioral Reviews, vol. 120, p. 583–594, 2021, ISSN: 01497634, (Publisher: Elsevier Ltd).
Résumé | Liens | BibTeX | Étiquettes: 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
@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}
}
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
5.
Cote, S. S. -P.; Paquette, G. R.; Neveu, S. -M.; Chartier, S.; Labbe, D. R.; Renaud, P.
Combining electroencephalography with plethysmography for classification of deviant sexual preferences. Article d'actes
Dans: Proceedings - 9th International Workshop on Biometrics and Forensics, IWBF 2021, Institute of Electrical and Electronics Engineers Inc., 2021, ISBN: 978-172819556-8 (ISBN), (Journal Abbreviation: Proc. - Int. Workshop Biom. Forensics, IWBF).
Résumé | Liens | BibTeX | Étiquettes: Biometrics, Classification, Classification (of information), Decision trees, Deviant sexual preferences, Dimensionality reduction, Electroencephalography, Electrophysiology, extraction, Extraction method, Machine learning, Plethysmography, Proof of concept, Psychophysiological measures, Standard protocols, Variable selection and extraction
@inproceedings{cote_combining_2021,
title = {Combining electroencephalography with plethysmography for classification of deviant sexual preferences.},
author = {S. S. -P. Cote and G. R. Paquette and S. -M. Neveu and S. Chartier and D. R. Labbe and P. Renaud},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85113855965&doi=10.1109%2fIWBF50991.2021.9465078&partnerID=40&md5=b545b2a6d22e32115ac179399188960e},
doi = {10.1109/IWBF50991.2021.9465078},
isbn = {978-172819556-8 (ISBN)},
year = {2021},
date = {2021-01-01},
booktitle = {Proceedings - 9th International Workshop on Biometrics and Forensics, IWBF 2021},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {Evaluating sexual preferences is a difficult task. Past researchrelied mostly on penile plethysmography (PPG). Even though this technique is the standard protocol used in most currentforensic settings, its usage showed mixed results. One way to improve PPG is the addition of other psychophysiological measures such as electroencephalography (EEG). However, EEG generates significant amount of data that hinders classification. Machine learning (ML) is nowadays an excellent tool to identify most discriminating variables and for classification. Therefore, it is proposed to use ML selection and extraction methods for dimensionality reduction and then to classify sexual preferences. Evidence from this proof of concept shows that using EEG and PPG together leads to better classification (85.6%) than using EEG (82.2%) or PPG individually (74.4%). The Random Forest (RF) classifier combined with the Principal Component Analysis (PCA) extraction method achieves a slightly higher general performance rate. This increase in performances opens the door for using more reliable biometric measures in the assessment of deviant sexual preferences. © 2021 IEEE.},
note = {Journal Abbreviation: Proc. - Int. Workshop Biom. Forensics, IWBF},
keywords = {Biometrics, Classification, Classification (of information), Decision trees, Deviant sexual preferences, Dimensionality reduction, Electroencephalography, Electrophysiology, extraction, Extraction method, Machine learning, Plethysmography, Proof of concept, Psychophysiological measures, Standard protocols, Variable selection and extraction},
pubstate = {published},
tppubtype = {inproceedings}
}
Evaluating sexual preferences is a difficult task. Past researchrelied mostly on penile plethysmography (PPG). Even though this technique is the standard protocol used in most currentforensic settings, its usage showed mixed results. One way to improve PPG is the addition of other psychophysiological measures such as electroencephalography (EEG). However, EEG generates significant amount of data that hinders classification. Machine learning (ML) is nowadays an excellent tool to identify most discriminating variables and for classification. Therefore, it is proposed to use ML selection and extraction methods for dimensionality reduction and then to classify sexual preferences. Evidence from this proof of concept shows that using EEG and PPG together leads to better classification (85.6%) than using EEG (82.2%) or PPG individually (74.4%). The Random Forest (RF) classifier combined with the Principal Component Analysis (PCA) extraction method achieves a slightly higher general performance rate. This increase in performances opens the door for using more reliable biometric measures in the assessment of deviant sexual preferences. © 2021 IEEE.
6.
Valverde, R.; Torres, B.; Motaghi, H.
IGI Global, 2018, ISBN: 978-1-5225-5220-8 1-5225-5219-7 978-1-5225-5219-2, (Publication Title: Quantum-Inspired Intelligent Systems for Multimedia Data Analysis).
Résumé | Liens | BibTeX | Étiquettes: Architecture-based, Computer anxiety, Data Analytics, Data collection mechanism, Electro-encephalogram (EEG), Electroencephalography, Information management, Learning management system, Quantum modeling, Surveys, Usability evaluation, Usability testing
@book{valverde_quantum_2018,
title = {A quantum NeuroIS data analytics architecture for the usability evaluation of learning management systems},
author = {R. Valverde and B. Torres and H. Motaghi},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049542254&doi=10.4018%2f978-1-5225-5219-2.ch009&partnerID=40&md5=8bc6e485175501b38a109ed03be0bedb},
doi = {10.4018/978-1-5225-5219-2.ch009},
isbn = {978-1-5225-5220-8 1-5225-5219-7 978-1-5225-5219-2},
year = {2018},
date = {2018-01-01},
publisher = {IGI Global},
abstract = {NeuroIS uses tools such as electroencephalogram (EEG) that can be used to measure high brainwave frequencies that can be linked to human anxiety. Past research showed that computer anxiety influences how users perceive ease of use of a learning management system (LMS). Although computer anxiety has been used successfully to evaluate the usability of LMS, the main data collection mechanisms proposed for its evaluation have been questionnaires. Questionnaires suffer from possible problems such as being inadequate to understand some forms of information such as emotions and honesty in the responses. Quantum-based approaches to consciousness have been very popular in the last years including the quantum model reduction in microtubules of Penrose and Hameroff (1995). The objective of the chapter is to propose an architecture based on a NeuroIS that collects data by using EEG from users and then use the collected data to perform analytics by using a quantum consciousness model proposed for computer anxiety measurements for the usability testing of a LMS. © 2018, IGI Global. All rights reserved.},
note = {Publication Title: Quantum-Inspired Intelligent Systems for Multimedia Data Analysis},
keywords = {Architecture-based, Computer anxiety, Data Analytics, Data collection mechanism, Electro-encephalogram (EEG), Electroencephalography, Information management, Learning management system, Quantum modeling, Surveys, Usability evaluation, Usability testing},
pubstate = {published},
tppubtype = {book}
}
NeuroIS uses tools such as electroencephalogram (EEG) that can be used to measure high brainwave frequencies that can be linked to human anxiety. Past research showed that computer anxiety influences how users perceive ease of use of a learning management system (LMS). Although computer anxiety has been used successfully to evaluate the usability of LMS, the main data collection mechanisms proposed for its evaluation have been questionnaires. Questionnaires suffer from possible problems such as being inadequate to understand some forms of information such as emotions and honesty in the responses. Quantum-based approaches to consciousness have been very popular in the last years including the quantum model reduction in microtubules of Penrose and Hameroff (1995). The objective of the chapter is to propose an architecture based on a NeuroIS that collects data by using EEG from users and then use the collected data to perform analytics by using a quantum consciousness model proposed for computer anxiety measurements for the usability testing of a LMS. © 2018, IGI Global. All rights reserved.
7.
Boukhalfi, T.; Joyal, C.; Bouchard, S.; Neveu, S. M.; Renaud, P.
Dans: A., Zaremba M. Sasiadek J. Dolgui (Ed.): IFAC-PapersOnLine, p. 46–51, 2015, (ISSN: 24058963 Issue: 3).
Résumé | Liens | BibTeX | Étiquettes: Acquisition, Analysis, brain computer interface, Data acquisition, Electroencephalography, eye tracking, Eye-tracking, Forensic, Forensic engineering, Heat maps, Interfaces (computer), Psychiatry, Real time, virtual reality
@inproceedings{boukhalfi_tools_2015,
title = {Tools and techniques for real-time data acquisition and analysis in brain computer interface studies using qEEG and eye tracking in virtual reality environment},
author = {T. Boukhalfi and C. Joyal and S. Bouchard and S. M. Neveu and P. Renaud},
editor = {Zaremba M. Sasiadek J. Dolgui A.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84953850845&doi=10.1016%2fj.ifacol.2015.06.056&partnerID=40&md5=5eaa3cab6df7946f02c74e4aded68eac},
doi = {10.1016/j.ifacol.2015.06.056},
year = {2015},
date = {2015-01-01},
booktitle = {IFAC-PapersOnLine},
volume = {28},
pages = {46–51},
abstract = {In this paper, we present the pipeline of data acquisition and analysis used in the ARViPL lab at the Montreal Philippe-Pinel Institute for different studies related to forensic psychiatry in Virtual Reality (VR) environment and we discuss the different challenges that we encounter during the experiments when combining different new technologies that help researchers to better understand the underlying mechanisms of various mental health disorders. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.},
note = {ISSN: 24058963
Issue: 3},
keywords = {Acquisition, Analysis, brain computer interface, Data acquisition, Electroencephalography, eye tracking, Eye-tracking, Forensic, Forensic engineering, Heat maps, Interfaces (computer), Psychiatry, Real time, virtual reality},
pubstate = {published},
tppubtype = {inproceedings}
}
In this paper, we present the pipeline of data acquisition and analysis used in the ARViPL lab at the Montreal Philippe-Pinel Institute for different studies related to forensic psychiatry in Virtual Reality (VR) environment and we discuss the different challenges that we encounter during the experiments when combining different new technologies that help researchers to better understand the underlying mechanisms of various mental health disorders. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.