Predicting mental imagery based BCI performance from personality, cognitive profile and neurophysiological patterns

Mental-Imagery based Brain-Computer Interfaces (MI-BCIs) allow their users to send commands to a computer using their brain-activity alone (typically measured by ElectroEncephaloGraphy— EEG), which is processed while they perform specific mental tasks. While very promising, MI-BCIs remain barely used outside laboratories because of the difficulty encountered by users to control them. Indeed, although some users obtain good control performances after training, a substantial proportion remains unable to reliably control an MI-BCI. This huge variability in user-performance led the community to look for predictors of MI-BCI control ability. However, these predictors were only explored for motor-imagery based BCIs, and mostly for a single training session per subject. In this study, 18 participants were instructed to learn to control an EEG-based MI-BCI by performing 3 MI-tasks, 2 of which were non-motor tasks, across 6 training sessions, on 6 different days. Relationships between the participants’ BCI control performances and their personality, cognitive profile and neurophysiological markers were explored. While no relevant relationships with neurophysiological markers were found, strong correlations between MI-BCI performances and mental-rotation scores (reflecting spatial abilities) were revealed. Also, a predictive model of MI-BCI performance based on psychometric questionnaire scores was proposed. A leave-one-subject-out cross validation process revealed the stability and reliability of this model: it enabled to predict participants’ performance with a mean error of less than 3 points. This study determined how users’ profiles impact their MI-BCI control ability and thus clears the way for designing novel MI-BCI training protocols, adapted to the profile of each user

EEG analytics for early detection of autism spectrum disorder: a data-driven approach

Autism spectrum disorder (ASD) is a complex and heterogeneous disorder, diagnosed on the basis of behavioral symptoms during the second year of life or later. Finding scalable biomarkers for early detection is challenging because of the variability in presentation of the disorder and the need for simple measurements that could be implemented routinely during well-baby checkups. EEG is a relatively easy-to-use, low cost brain measurement tool that is being increasingly explored as a potential clinical tool for monitoring atypical brain development. EEG measurements were collected from 99 infants with an older sibling diagnosed with ASD, and 89 low risk controls, beginning at 3 months of age and continuing until 36 months of age. Nonlinear features were computed from EEG signals and used as input to statistical learning methods. Prediction of the clinical diagnostic outcome of ASD or not ASD was highly accurate when using EEG measurements from as early as 3 months of age. Specificity, sensitivity and PPV were high, exceeding 95% at some ages. Prediction of ADOS calibrated severity scores for all infants in the study using only EEG data taken as early as 3 months of age was strongly correlated with the actual measured scores. This suggests that useful digital biomarkers might be extracted from EEG measurements.This research was supported by National Institute of Mental Health (NIMH) grant R21 MH 093753 (to WJB), National Institute on Deafness and Other Communication Disorders (NIDCD) grant R21 DC08647 (to HTF), NIDCD grant R01 DC 10290 (to HTF and CAN) and a grant from the Simons Foundation (to CAN, HTF, and WJB). We are especially grateful to the staff and students who worked on the study and to the families who participated. (R21 MH 093753 - National Institute of Mental Health (NIMH); R21 DC08647 - National Institute on Deafness and Other Communication Disorders (NIDCD); R01 DC 10290 - NIDCD; Simons Foundation)Published versio

An EEG study on emotional intelligence and advertising message effectiveness

Some electroencephalography (EEG) studies have investigated emotional intelligence (EI), but none have examined the relationships between EI and commercial advertising messages and related consumer behaviors. This study combines brain (EEG) techniques with an EI psychometric to explore the brain responses associated with a range of advertisements. A group of 45 participants (23females, 22males) had their EEG recorded while watching a series of advertisements selected from various marketing categories such as community interests, celebrities, food/drink, and social issues. Participants were also categorized as high or low in emotional intelligence (n = 34). The EEG data analysis was centered on rating decision-making in order to measure brain responses associated with advertising information processing for both groups. The findings suggest that participants with high and low emotional intelligence (EI) were attentive to different types of advertising messages. The two EI groups demonstrated preferences for “people” or “object,” related advertising information. This suggests that differences in consumer perception and emotions may suggest why certain advertising material or marketing strategies are effective or not

Nägemistaju automaatsete protsesside eksperimentaalne uurimine

Väitekirja elektrooniline versioon ei sisalda publikatsiooneVäitekiri keskendub nägemistaju protsesside eksperimentaalsele uurimisele, mis on suuremal või vähemal määral automaatsed. Uurimistöös on kasutatud erinevaid eksperimentaalseid katseparadigmasid ja katsestiimuleid ning nii käitumuslikke- kui ka ajukuvamismeetodeid. Esimesed kolm empiirilist uurimust käsitlevad liikumisinformatsiooni töötlust, mis on evolutsiooni käigus kujunenud üheks olulisemaks baasprotsessiks nägemistajus. Esmalt huvitas meid, kuidas avastatakse liikuva objekti suunamuutusi, kui samal ajal toimub ka taustal liikumine (Uurimus I). Nägemistaju uurijad on pikka aega arvanud, et liikumist arvutatakse alati mõne välise objekti või tausta suhtes. Meie uurimistulemused ei kinnitanud taolise suhtelise liikumise printsiibi paikapidavust ning toetavad pigem seisukohta, et eesmärkobjekti liikumisinformatsiooni töötlus on automaatne protsess, mis tuvastab silma põhjas toimuvaid nihkeid, ja taustal toimuv seda eriti ei mõjuta. Teise uurimuse tulemused (Uurimus II) näitasid, et nägemissüsteem töötleb väga edukalt ka seda liikumisinformatsiooni, millele vaatleja teadlikult tähelepanu ei pööra. See tähendab, et samal ajal, kui inimene on mõne tähelepanu hõlmava tegevusega ametis, suudab tema aju taustal toimuvaid sündmusi automaatselt registreerida. Igapäevaselt on inimese nägemisväljas alati palju erinevaid objekte, millel on erinevad omadused, mistõttu järgmiseks huvitas meid (Uurimus III), kuidas ühe tunnuse (antud juhul värvimuutuse) töötlemist mõjutab mõne teise tunnusega toimuv (antud juhul liikumiskiiruse) muutus. Näitasime, et objekti liikumine parandas sama objekti värvimuutuse avastamist, mis viitab, et nende kahe omaduse töötlemine ajus ei ole päris eraldiseisev protsess. Samuti tähendab taoline tulemus, et hoolimata ühele tunnusele keskendumisest ei suuda inimene ignoreerida teist tähelepanu tõmbavat tunnust (liikumine), mis viitab taas kord automaatsetele töötlusprotsessidele. Neljas uurimus keskendus emotsionaalsete näoväljenduste töötlusele, kuna need kannavad keskkonnas hakkamasaamiseks vajalikke sotsiaalseid signaale, mistõttu on alust arvata, et nende töötlus on kujunenud suuresti automaatseks protsessiks. Näitasime, et emotsiooni väljendavaid nägusid avastati kiiremini ja kergemini kui neutraalse ilmega nägusid ning et vihane nägu tõmbas rohkem tähelepanu kui rõõmus (Uurimus IV). Väitekirja viimane osa puudutab visuaalset lahknevusnegatiivsust (ingl Visual Mismatch Negativity ehk vMMN), mis näitab aju võimet avastada automaatselt erinevusi enda loodud mudelist ümbritseva keskkonna kohta. Selle automaatse erinevuse avastamise mehhanismi uurimisse andsid oma panuse nii Uurimus II kui Uurimus IV, mis mõlemad pakuvad välja tõendusi vMMN tekkimise kohta eri tingimustel ja katseparadigmades ning ka vajalikke metodoloogilisi täiendusi. Uurimus V on esimene kogu siiani ilmunud temaatilist teadustööd hõlmav ülevaateartikkel ja metaanalüüs visuaalsest lahknevusnegatiivsusest psühhiaatriliste ja neuroloogiliste haiguste korral, mis panustab oluliselt visuaalse lahknevusnegatiivsuse valdkonna arengusse.The research presented and discussed in the thesis is an experimental exploration of processes in visual perception, which all display a considerable amount of automaticity. These processes are targeted from different angles using different experimental paradigms and stimuli, and by measuring both behavioural and brain responses. In the first three empirical studies, the focus is on motion detection that is regarded one of the most basic processes shaped by evolution. Study I investigated how motion information of an object is processed in the presence of background motion. Although it is widely believed that no motion can be perceived without establishing a frame of reference with other objects or motion on the background, our results found no support for relative motion principle. This finding speaks in favour of a simple and automatic process of detecting motion, which is largely insensitive to the surrounding context. Study II shows that the visual system is built to automatically process motion information that is outside of our attentional focus. This means that even if we are concentrating on some task, our brain constantly monitors the surrounding environment. Study III addressed the question of what happens when multiple stimulus qualities (motion and colour) are present and varied, which is the everyday reality of our visual input. We showed that velocity facilitated the detection of colour changes, which suggests that processing motion and colour is not entirely isolated. These results also indicate that it is hard to ignore motion information, and processing it is rather automatically initiated. The fourth empirical study focusses on another example of visual input that is processed in a rather automatic way and carries high survival value – emotional expressions. In Study IV, participants detected emotional facial expressions faster and more easily compared with neutral facial expressions, with a tendency towards more automatic attention to angry faces. In addition, we investigated the emergence of visual mismatch negativity (vMMN) that is one of the most objective and efficient methods for analysing automatic processes in the brain. Study II and Study IV proposed several methodological gains for registering this automatic change-detection mechanism. Study V is an important contribution to the vMMN research field as it is the first comprehensive review and meta-analysis of the vMMN studies in psychiatric and neurological disorders

Psychic embedding — vision and delusion

The paper introduces the idea that the human brain may apply complex mathematical modules in order to process and understand the world. We speculate that the substrate of what appears outwardly as intuition, or prophetic power, may be a mathematical apparatus such as time-delay embedding. In this context, predictive accuracy may be the reflection of an appropriate choice of the embedding parameters. We further put this in the perspective of mental illness, and search for the possible differences between good intuition and delusive ideation. We speculate that the task at which delusional schizophrenic patients falter is not necessarily of perception, but rather of model selection. Failure of the psychotic patient to correctly choose the embedding parameters may readily lead to misinterpretation of an accurate perception through an altered reconstructed of the object perceived

Positive emotion broadens attention focus through decreased position-specific spatial encoding in early visual cortex: evidence from ERPs

Recent evidence has suggested that not only stimulus-specific attributes or top-down expectations can modulate attention selection processes, but also the actual mood state of the participant. In this study, we tested the prediction that the induction of positive mood can dynamically influence attention allocation and, in turn, modulate early stimulus sensory processing in primary visual cortex (V1). High-density visual event-related potentials (ERPs) were recorded while participants performed a demanding task at fixation and were presented with peripheral irrelevant visual textures, whose position was systematically varied in the upper visual field (close, medium, or far relative to fixation). Either a neutral or a positive mood was reliably induced and maintained throughout the experimental session. The ERP results showed that the earliest retinotopic component following stimulus onset (C1) strongly varied in topography as a function of the position of the peripheral distractor, in agreement with a near-far spatial gradient. However, this effect was altered for participants in a positive relative to a neutral mood. On the contrary, positive mood did not modulate attention allocation for the central (task-relevant) stimuli, as reflected by the P300 component. We ran a control behavioral experiment confirming that positive emotion selectively impaired attention allocation to the peripheral distractors. These results suggest a mood-dependent tuning of position-specific encoding in V1 rapidly following stimulus onset. We discuss these results against the dominant broaden-and-build theory