Locked-in syndrome (LIS) is a condition characterized by total or near-total paralysis with preserved cognitive and somatosensory function. For the locked-in, brain-machine interfaces (BMI) provide a level of restored communication and interaction with the world, though this technology has not reached its fullest potential. Several streams of research explore improving BMI performance but very little attention has been given to the paradigms implemented and the resulting constraints imposed on the users. Learning new mental tasks, constant use of external stimuli, and high attentional and cognitive processing loads are common demands imposed by BMI. These paradigm constraints negatively affect BMI performance by locked-in patients. In an effort to develop simpler and more reliable BMI for those suffering from LIS, this dissertation explores using error-related potentials, the neural correlates of error awareness, as an access pathway for adaptive decoding and direct volitional control. In the first part of this thesis we characterize error-related local field potentials (eLFP) and implement a real-time decoder error detection (DED) system using eLFP while non-human primates controlled a saccade BMI. Our results show specific traits in the eLFP that bridge current knowledge of non-BMI evoked error-related potentials with error-potentials evoked during BMI control. Moreover, we successfully perform real-time DED via, to our knowledge, the first real-time LFP-based DED system integrated into an invasive BMI, demonstrating that error-based adaptive decoding can become a standard feature in BMI design. In the second part of this thesis, we focus on employing electroencephalography error-related potentials (ErrP) for direct volitional control. These signals were employed as an indicator of the user’s intentions under a closed-loop binary-choice robot reaching task. Although this approach is technically challenging, our results demonstrate that ErrP can be used for direct control via binary selection and, given the appropriate levels of task engagement and agency, single-trial closed-loop ErrP decoding is possible. Taken together, this work contributes to a deeper understanding of error-related potentials evoked during BMI control and opens new avenues of research for employing ErrP as a direct control signal for BMI. For the locked-in community, these advancements could foster the development of real-time intuitive brain-machine control.

The current study evaluates the effectiveness of a Brain-Computer Interface (BCI) system that operates by detecting a P300 elicited by one of four randomly presented stimuli (i.e., YES, NO, PASS, END). Two groups of participants were tested. The first group included three ALS patients that varied in degree of disability, but all retained the ability to communicate; the second group included three Non-ALS controls. Each participant participated in ten experimental sessions during a period of approximately 6 weeks. Sessions were conducted either at the participant's home or in the lab. During each run the participant's task was to attend to one stimulus and disregard the other three. Stimuli were presented auditorily, visually, or in both modes. Additionally, on each run, the experimenter would either tell the participant which stimulus to focus on, or ask the participant a question and the participant would focus on the correct "YES/NO" answer to the question. Overall, for each participant, the ERPs elicited by the target stimuli could be discriminated from the non-target stimuli; however, less variability was observed in the Non-ALS group. Comparing across sessions, the within session variability was lower than across session variability. In addition, waveform morphology varied as a function of the presentation mode, but not in a similar pattern for each participant. Offline and simulated online classification algorithms conducted using step-wise discriminant analysis produced results suggesting the potential for online classification performance at levels acceptable for communication. Future investigations will begin to focus on testing online classification performance with real-time feedback, and continuing to examine stimulus properties to determine how to maximize P300 amplitude for individual users.

A brain-computer interface (BCI) allows individuals to communicate through the modulation of regional brain activity. Clinical near-infrared spectroscopy (NIRS) is used to monitor changes in cerebral blood oxygenation due to functional activation. It was hypothesized that visually-cued emotional induction tasks can elicit detectable activity in the prefrontal cortex. Data were collected from eleven participants as they performed positively and negatively-valenced emotional induction tasks. Baseline and activation trials were classified offline with accuracies from 75.0-96.7% after applying a feature selection algorithm to determine optimal performance parameters for each participant. Feature selection identified common discriminatory features across participants and relationships between performance parameters. Additionally, classification accuracy was used to quantify NIRS hemodynamic response latency. Significant increases in classification rates were found as early as 2.5 s after initial stimulus presentation. These results suggest the potential application of emotional induction as a NIRS-BCI control paradigm.

A brain-computer interface (BCI) allows individuals to communicate through the modulation of regional brain activity. Clinical near-infrared spectroscopy (NIRS) is used to monitor changes in cerebral blood oxygenation due to functional activation. It was hypothesized that visually-cued emotional induction tasks can elicit detectable activity in the prefrontal cortex. Data were collected from eleven participants as they performed positively and negatively-valenced emotional induction tasks. Baseline and activation trials were classified offline with accuracies from 75.0-96.7% after applying a feature selection algorithm to determine optimal performance parameters for each participant. Feature selection identified common discriminatory features across participants and relationships between performance parameters. Additionally, classification accuracy was used to quantify NIRS hemodynamic response latency. Significant increases in classification rates were found as early as 2.5 s after initial stimulus presentation. These results suggest the potential application of emotional induction as a NIRS-BCI control paradigm.

Brain-computer interfaces (BCIs) are very convenient tools to assess locked-in (LIS) and completely locked-in state (CLIS) patients' hidden states of consciousness. For the time being, there is no ground-truth data in respect to these states for above-mentioned patients. This lack of gold standard makes this problem particularly challenging. In addition to consciousness assessment, BCIs also provide them with a communication device that does not require the presence of motor responses, which they are lacking. Communication plays an important role in the patients' quality of life and prognosis. Significant progress have been made to provide them with EEG-based BCIs in particular. Nonetheless, the majority of existing studies directly dive into the communication part without assessing if the patient is even conscious. Additionally, the few studies that do essentially use evoked brain potentials, mostly the P300, that necessitates the patient's voluntary and active participation to be elicited. Patients are easily fatigued, and would consequently be less successful during the main communication task. Furthermore, when the consciousness states are determined using resting state data, only one or two features were used. In this thesis, different sets of EEG features are used to assess the consciousness level of CLIS patients using resting-state data. This is done as a preliminary step that needed to be succeeded in order to engage to the next step, communication with the patient. In other words, the 'conversation' is initiated only if the patient is sufficiently conscious. This variety of EEG features is utilised to increase the probability of correctly estimating the patients' consciousness states. Indeed, each of them captures a particular signal attribute, and combining them would allow the collection of different hidden characteristics that could have not been obtained from a single feature. Furthermore, the proposed method should allow to determine if communication shall be initiated at a specific time with the patient. The EEG features used are frequency-based, complexity related and connectivity metrics. Besides, instead of analysing results from individual channels or specific brain regions, the global activity of the brain is assessed. The estimated consciousness levels are then obtained by applying two different soft-clustering analysis methods, namely Fuzzy c-means (FCM) and Gaussian Mixture Models (GMM), to the individual features and ensembling their results using their average or their product. The proposed approach is first applied to EEG data recorded from patients with unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS) (patients with disorders of consciousness (DoC)) to evaluate its performance. It is subsequently applied to data from one CLIS patient that is unique in its kind because it contains a time frame during which the experimenters affirmed that he was conscious. Finally, it is used to estimate the levels of consciousness of nine other CLIS patients. The obtained results revealed that the presented approach was able to take into account the variations of the different features and deduce a unique output taking into consideration the individual features contributions. Some of them performed better than others, which is not surprising since each person is different. It was also able to draw very accurate estimations of the level of consciousness under specific conditions. The approach presented in this thesis provides an additional tool for diagnosis to the medical staff. Furthermore, when implemented online, it would enable to determine the optimal time to engage in communication with CLIS patients. Moreover, it could possibly be used to predict patients' cognitive decline and/or death.

The aim of the present study was to characterize participants’ abilities to answer binary yes/no questions by mentally manipulating imagery to produce imagined changes in luminance, which would in turn cause reflexive perturbations in pupil diameter. First, a paired association was established with participants, linking “yes” responses with imagining a “sunny sky” and “no” responses with imagining a “dark room”. Participants (N=20) then answered 16 yes/no questions using this response method, in place of providing verbal or gestural (e.g., head nod) answers. Pupil diameters were recorded for a period of 8000 ms following each stimulus question while participants maintained the mental image that corresponded with their answer. We hypothesized that on average, “no” responses would yield a pupil dilation and increased diameter relative to baseline, while “yes” responses would instead result in constrictions and smaller pupil diameters compared to baseline. A 2-factor repeated measures analysis of variance (ANOVA), where time was one factor and response type (i.e., yes or no) was the other, revealed a statistically significant interaction of time and response type, a significant main effect of time, and a trend toward significance for response type in aggregated group data. Item level discrimination consisted of comparing the mean pupil diameter in response to a single item for a single participant (e.g., “yes” response on one trial) to the mean pupil diameter of all contrasting responses for that same participant (e.g., all “no” response trials). This method achieved a 64.5% discrimination accuracy. This investigation affirmed the plausibility of leveraging pupillometry and luminance-based mental imagery in favor of an alternative communication system for individuals who are locked-in, as well as its potential as a screening tool. However, further investigation is warranted prior to its implementation. / Communication Sciences

L'objectif de la thèse est de déterminer, du point de vue subjectif, ce qui constitue le vécu identitaire. Conscients que la notion d'identité a été travaillée principalement du point de vue objectif en épistémologie, nous voudrions nous pencher plus avant sur l'identité telle qu'elle est vécue par le sujet. Il nous semble que ce concept prend sens pour le sujet à la fois dans le temps, comme continuité d'une présence à soi, et dans un sentiment d'appartenance ou de reconnaissance indissociable de l'expérience incarnée d'être soi. Dans une conception naturaliste de l'identité, nous illustrerons notre propos philosophique par l'étude expérimentale de deux pathologies qui affectent directement le sentiment d'identité du sujet, l'une dans le sens d'une fragmentation de son histoire qui perturbe alors l'appropriation d'un vécu comme sien propre (maladie d'Alzheimer), l'autre dans le sens d'une dépossession du corps comme outil de la volonté qui menace alors l'appropriation du corps comme corps propre (locked-in syndrome). Cette étude se situe donc d'emblée à l'intersection des philosophies du corps et des sciences cognitives contemporaines, proposant un renouveau épistémologique du concept d'identité.

Embodied approaches to cognition consider themselves as alternatives to a brain-bound view of cognition. They decisively emphasize that the brain is not the minimal basis for cognition, but that the body plays a crucial role as well. But what do we actually mean by “the body” and to what extent is it a necessary condition for cognition? Is bodily action equated with movement? Is the human body just a biological phenomenon? How is it related to the human self and sociality? This thesis explores these questions by confronting embodied cognitive science with Locked-in Syndrome (LIS), a case of global paralysis, which despite the lack of voluntarily bodily action seems to leave the patient cognitively intact. I suggest that LIS poses a challenge to embodied cognitive science putting into question our basic assumptions on what it means to be a human cognitive system. A body without movement and a self whose connection to the social sphere is radically impoverished – how can we make sense of this? LIS challenges the concepts by which we describe the structure and various dimensions of cognition and it invites us to make explicit the background epistemology and general perspective through which we relate the different aspects of cognition. First, I provide an overview of the philosophy of cognitive science, from the orthodox perspective up to recent embodied cognitive science. I then introduce and clarify the enactive approach, an integrative framework for cognitive science that also serves as the epistemological basis of this thesis. Based on the different states of LIS I formulate a challenge to embodied cognitive science and discuss how the sensorimotor, functionalist and phenomenological approach to embodiment account for it. The discussion casts doubt on the assumption that a body has mainly to do with movement and it reposes the question how tool-use figures in cognition. It also brings to attention the dimension of bodily subjectivity and raises a much-neglected issue in recent cognitive science: the role of the body in social interactions. I show that these approaches to embodiment entail restrictive or loose notions of the body and are not fully able to account for cognition in LIS. I formulate a proposal for an enactive concept of the body integrating aspects from the sensorimotor and phenomenological approach to the body. I defend the idea that the enactive approach is the best framework in embodied cognitive science to counter the challenge posed by LIS and BCI. However, since embodied cognitive science entails an individualistic perspective not fully taking into account that humans are embedded in a social environment the question how the body matters in social interaction can also not be resolved from an enactive perspective on the body. In the last part of this thesis I thus propose transcending the level of individual embodiment. I make suggestions for elaborating on the enactive notion for the cognitive system (autonomy) from a social perspective. I propose to conceive of human mind in terms of a network that is based on the enaction of social processes of distinction and participation. Based on this notion I show how we arrive at an understanding of the human cognitive system which could ultimately account for the basic challenge posited by LIS – the clarification and interrelation of the concepts of body, self and sociality. In the last chapter I provide support for the plausibility for this proposal by applying it to another empirical context, namely psychiatry. What we think about the nature of human mind sets the ground for our thinking about breakdowns and what happens in cases when it does not work. I explore possible implications of the concept of socially enacted human autonomy for mental disorders in general, and for schizophrenia in particular.

People withmobilityandspeechrestrictionssimultaneoushaveverbalcommunicationandbody language impaired.Inthemostextremecasesthepatientsaredeprivedofalltheirmovements and speechcapabilities.ThissituationischaracterizedastheLocked-inSyndrome(LIS).The augmentativeandalternativecommunicationtechnologiesprovidemethodsandsoftwaresthat allowthesepatientstocommunicatewiththeexternalenvironmentandpeoplearoundthem. Among thevariousmethodsandexistingcommunicationprogramswecanhighlightthevirtual keyboard.However,datainputusingthiskindofkeyboardisconsiderablyslowerandmore tiresome forpeoplewithLIS.Thisworkaimstobuildanassistivevirtualkeyboardtoassist patients withseveremobilityrestrictionsandspeechtocommunicate.Toachievethisgoalit wasconductedtwosystematicreviewsandaliteraturereview.Fromtheknowledgegained from theseresearchswemodeledanddevelopedanassistivevirtualkeyboard.Moreover,we designed andimplementedanevolutionarymethodologythatallowsthekeyboardtoadaptitself to user svocabularyandwritingmode.Finally,anexperimentthatcomparesthetraditional method keyboardsoptimizationwiththemethodologyproposedinthisthesiswascarriedout. / Pessoas comrestriçõesmotorasedefalasimultâneastêmacomunicaçãoverbalealinguagem corporal prejudicadas.Noscasosmaisextremosopacienteéprivadodetodososseusmovimen- tos edacapacidadedefala.EssasituaçãoécaracterizadacomoaSíndromedoEncarceramento (SE). Astecnologiasdecomunicaçãoaumentativaealternativasãoresponsáveisporproporcio- narem métodose softwares que possibilitamacomunicaçãodospacientescomoambienteeas pessoas queoscercam.Entreosváriosmétodoseprogramasdecomunicaçãoexistentespode-se destacar otecladovirtual.Porém,aentradadedadosutilizandotecladosvirtuaiséconsidera- velmentemaislentaecansativaparapessoascomSE.Oobjetivodestetrabalhoéconstruirum teclado virtualassistivoparaauxiliarpacientescomrestriçõesmotorasgravesedefalaaseco- municarem. Paraatingiresseobjetivoforamrealizadasduasrevisõessistemáticaseumarevisão de literatura.Apartirdoconhecimentoadquiridodessasrevisõesfoimodeladoedesenvolvido um tecladovirtualassistivo.Alémdisso,foielaboradaeimplementadaumametodologiaevolu- tivaquepermiteotecladoseadaptaraovocabulárioeomododeescritadousuário.Finalmente, foi realizadoumexperimentoquecomparaométodotradicionaldeotimizaçãodetecladoscom a metodologiapropostanestatese. / Doutor em Ciências