Le trouble déficitaire de l'attention avec hyperactivité (TDAH) et le tabagisme ont un lien établi. Les personnes atteintes d’un TDAH sont plus portées à développer une dépendance à la cigarette, à débuter le tabagisme plus jeune et ont plus de difficultés à cesser de fumer. Il est maintenant connu que le traitement du TDAH modifie ces interactions. Bien que les psychostimulants soient le traitement pharmacologique de choix pour le TDAH, les effets secondaires indésirables de ces substances réduisent considérablement l’utilisation par ceux qui veulent cesser de fumer, surtout s’ils utilisent déjà des substances ayant des propriétés stimulantes, tel que la nicotine, pour les aider. Cette étude a comme objectif d’évaluer l’efficacité potentielle d’un traitement de neurofeedback chez des adultes atteints d’un TDAH et qui, malgré l’utilisation d’un timbre de nicotine, n’arrivaient toujours pas à cesser de fumer. Quatre participantes qui ont rencontré les critères de recherche pour le TDAH ont reçu 12 à 14 séances de neurofeedback pendant qu’elles continuaient un traitement avec un timbre de nicotine. L’efficacité de l’intervention en neurofeedback est évaluée selon un devis de recherche à cas unique avec lignes de base multiples établies en fonction des participants. L’analyse post-intervention révèle que trois des quatre participantes ont réduit de façon significative leur dépendance sur la nicotine à la suite du traitement. Le neurofeedback déjà connu comme traitement efficace du TDAH, dans le cas de dépendance à la nicotine, peut améliorer la tolérance aux symptômes de sevrage en passant par une amélioration de l’attention.

Autism is a disorder that impairs the development of a person's ability to interact with other people and to relate productively with the outside world. There are many types of interventions being used to treat autism, but there are no cures or definitive treatments for this disorder. A biological theoretical foundation was the basis of this study, as recent neuroimaging techniques have demonstrated that autism is a neurological disorder that reveals distinct abnormalities in the brain. The purpose of this study was to examine the efficacy of neurofeedback (NFB) in the treatment of autism. NFB has shown promise of improving the negative symptoms associated with autism, such as repetitive behaviors, aggression, problems with communication, and social ineptness. This study reviewed the results of children diagnosed with autism who were exposed to NFB. Archived data were obtained from a neurofeedback clinic in California. Thirty-eight pre and posttreatment brain maps, collected from individuals treated with NFB, demonstrated that NFB helped brainwaves to settle into a more normalized pattern. Treatment effectiveness was analyzed using binomial expansion (BE), and 9 parents completed the Autism Treatment Evaluation Checklist (ATEC). Clinician notes were also used to provide qualitative information. The findings of this study may impact social change by providing support for NFB as an effective treatment for autism. NFB may be a potential non-medical, noninvasive, and long-lasting approach for those afflicted with autism.

Near-infrared spectroscopy (NIRS) is an emerging non-invasive brain-computer interface (BCI) modality that measures changes in hemoglobin concentrations in neurocortical tissue. Previous NIRS studies have not employed real-time feedback with online classification, a combination which would allow users to alter their mental strategy on the fly. This thesis reports the results of two online studies. The first study contrasted online classification of prefrontal hemodynamics using an artificial neural network (ANN) and a hidden Markov model-based (HMM) classifier. The second study measured the accuracy of an online linear discriminant classifier. In study 1, only the ANN classifier facilitated online classification rates greater than chance (p=0.0289). In study 2, a new feedback system and experimental protocol led to improved classification rates over those of the first study (p=5.1*10^(-5)). While control over instantaneously generated feedback in online NIRS-BCIs has been demonstrated, factors such as user frustration, mental fatigue, and restrictions on ambient lighting may compromise performance.

Near-infrared spectroscopy (NIRS) is an emerging non-invasive brain-computer interface (BCI) modality that measures changes in hemoglobin concentrations in neurocortical tissue. Previous NIRS studies have not employed real-time feedback with online classification, a combination which would allow users to alter their mental strategy on the fly. This thesis reports the results of two online studies. The first study contrasted online classification of prefrontal hemodynamics using an artificial neural network (ANN) and a hidden Markov model-based (HMM) classifier. The second study measured the accuracy of an online linear discriminant classifier. In study 1, only the ANN classifier facilitated online classification rates greater than chance (p=0.0289). In study 2, a new feedback system and experimental protocol led to improved classification rates over those of the first study (p=5.1*10^(-5)). While control over instantaneously generated feedback in online NIRS-BCIs has been demonstrated, factors such as user frustration, mental fatigue, and restrictions on ambient lighting may compromise performance.

Le neurofeedback est typiquement considéré par le monde médical comme une technique prometteuse dans le traitement du TDAH, mais dont l'efficacité spécifique n'est pas suffisamment bien établie. La présente étude cherche à déterminer des effets spécifiques au neurofeedback sur le fonctionnement intellectuel et sur les comportements d'enfants présentant un TDAH. Pour ce faire, deux expérimentations ont été réalisées auprès de 46 enfants au total (15 enfants lors de la première expérimentation et 31 pour la deuxième), âgés de 7 à 13 ans et ayant un diagnostic de TDAH (tous déjà traités avec une médication psychostimulante). L'entraînement de neurofeedback visait à augmenter l'amplitude du rythme sensori-moteur (12-15 Hz) et à diminuer l'amplitude des ondes Thêta (4-8 Hz) au-dessus du cortex sensori-moteur droit (C4). La première expérimentation impliquait des enfants recevant le neurofeedback et d'autres en liste d'attente. Elle visait d'abord à récolter les enregistrements EEG requis pour la condition placebo de l'étude suivante et à identifier les variables les plus susceptibles de montrer l'efficacité du traitement. Elle pouvait aussi déjà démontrer une certaine efficacité du protocole de neurofeedback choisi. En cela et malgré la prise en compte du grand nombre de variables examinées, deux sous-échelles « TDAH » du questionnaire CBCL complété par les parents ont montré des améliorations significatives pour les enfants ayant bénéficié du neurofeedback. Le questionnaire DuPaul rempli par les parents montrait aussi un effet crédible, mais en deçà du seuil statistique corrigé pour le grand nombre de variables examinées dans cette étude préliminaire. La deuxième expérimentation reprenait les mêmes conditions en ajoutant un groupe placebo avec double insu (concernant les groupes placebo et neurofeedback). Le but de la condition placebo était de déterminer que c'est bien la modulation de l'EEG et non la relation établie avec les parents du groupe entraîné qui amène les améliorations rapportées. Les enfants sélectionnés ont été répartis aléatoirement en trois groupes (vrai neurofeedback, neurofeedback placebo, attente). La tendance vers un effet significatif au DuPaul-parent de la première étude et la contribution de l'entraînement de l'EEG ont été confirmées à l'étude 2 puisque des améliorations significatives ont été observées pour le groupe d'enfants ayant bénéficié du vrai neurofeedback par rapport aux deux groupes contrôles sur deux des trois sous-échelles du questionnaire DuPaul-parent (« Inattention » et « Totale »). Toutefois, les améliorations significatives obtenues lors de la première expérimentation au CBCL n'ont pas été reproduites, ce qui demeure inexpliqué. Des gains aux échelles partielles « Compréhension verbale » et « Mémoire de travail » ainsi qu'à l'échelle globale de l'épreuve d'intelligence ont aussi été observés, ce qui n'avait pas été le cas lors de la première expérimentation. Notons toutefois que ces gains n'étaient pas suffisamment importants pour franchir le seuil de signification avec la correction de Bonferroni (p ≤ .01) spécifiée a priori. En conclusion, les résultats obtenus mettent en évidence des effets spécifiques au neurofeedback agissant notamment sur les symptômes comportementaux du TDAH. Rappelons que ces effets n'ont pas été observés pour le groupe en condition placebo. D'autres recherches sont nécessaires pour reproduire ces résultats et éventuellement, mieux comprendre le fonctionnement de ce traitement afin d'être en mesure de l'utiliser de façon optimale. ______________________________________________________________________________ MOTS-CLÉS DE L’AUTEUR : Neurofeedback, TDAH, enfants, placebo

<p>The brain’s dopaminergic system is critical to adaptive behaviors, and is centrally implicated in various pathologies. For decades, research has aimed at better characterizing what drives the mesolimbic dopamine system and the resulting influence on brain physiology and behavior in both humans and animals. To date, the dominant modes of research have relied on extrinsic approaches: pharmacological manipulations, direct brain stimulation, or delivering behavioral incentives in laboratory tasks. A critical open question concerns whether individuals can modulate activation within this system volitionally. That is, can individuals use self-generated thoughts and imagery to invigorate this system on their own? This process can be referred to as “cognitive neurostimulation” -- a precise and non-invasive stimulation of neural systems via cognitive and behavioral strategies. And if not, can they be taught to do so? Recent technological advances make it feasible to present human participants with information about ongoing neural activations in a fast and spatially precise manner. Such feedback signals might enable individuals to eventually learn to control neural systems via fine-tuning of behavioral strategies. The studies described herein investigate whether individuals can learn to volitionally invigorate activation within the mesolimbic reward network. We demonstrate that under the right training context, individuals can successfully learn to generate cognitive states that elicit and sustain activation in the ventral tegmental area (VTA), the source of dopamine production within the mesolimbic network. Although participants were explicitly trained to increase VTA activation, multiple mesolimbic regions exhibited increased connectivity during and after training. Together, these findings suggest new frameworks for aligning psychological and biological perspectives, and for understanding and harnessing the power of neuromodulatory systems.</p> / Dissertation

An important clinical research question to be answered in the field of neurofeedback (NF) is whether amplitude training affects connectivity between cortical sites. This study hypothesizes that, following NF amplitude training, there will be a difference in QEEG coherence and phase measures between NF training done using referential montages and using sequential montages. The study examined case files of 16 adult clients from the University of North Texas Neurotherapy Lab who had received NF training that consisted of either referential or sequential placement amplitude training (no coherence training) and who received both pre- and post- treatment QEEGs. Sixty-eight percent of the cases consisted of referential placements, while 34% of the cases consisted of sequential placements. All frontal site phase and coherence abnormal z-scores at pre-treatment were converted to deviation scores and compared by general linear model analysis of variance to post-treatment deviation scores. Effect size r-values and eta square values indicate that differences between referential and sequential electrode placements after NF amplitude training are moderately high. This study shows that referential placements tend to increase phase scores and decrease coherence scores, while sequential placements tend to decrease phase scores and increase coherence scores.

I obtained 182 session graphs from 10 client records from a university-based neurotherapy clinic and from a private practitioner. These graphs were used to examine the relationship of therapeutic crossover activity (defined as at least 3 minutes in duration and at least 1μv in amplitude) with and without predetermined amplitude thresholds of beta (15-20Hz) to client reports of imagery and to treatment outcomes. Crosstab analysis revealed that significantly more reports of imagery were observed in the therapeutic crossover with beta condition and that higher amplitudes of slower brainwave activity correlated with progression to deeper states of consciousness. Multi-level modeling revealed a significant interaction between therapeutic crossover activity, higher beta frequency amplitude, and reported salient imagery. Due to small sample size, significance testing was not deemed appropriate. However, observation in change of pre-post scores suggested that individuals who experienced more therapeutic crossover with sufficient beta amplitude conditions had greater improvements on post-test measures (BAI, BDI, BHS, PSQI and MMPI) than those with no or few crossovers. Higher amplitudes of slower brainwave activity correlated with progression to deeper states of consciousness, with delta amplitude positively correlating with transpersonal states. Reports of imagery and/or biographical memory are much more likely to occur during theta-alpha crossover activity characterized by 3 minutes or more in duration, one microvolt or more in amplitude, and 3.75μv amplitude or more of beta. This defined therapeutic crossover condition does appear to facilitate recall of imagery and memories during alpha-theta neurofeedback and was related to better treatment outcomes.

Tato práce je shrnutím existujících přístupů pro zpracování EEG signálu za účelem EEG biofeedbacku a dále popisuje návrh a implementaci vlastní aplikace pro EEG biofeedback se zaměřením na trénink pozornosti. Dále obsahuje případovou studii provedenou na neurotypickém studentovi a studentovi s ADHD, která zkoumá vliv implementované aplikace na měřený EEG signál subjektů.

Emotion dysregulation plays a central role in psychopathology (B. Bradley et al., 2011) and has been linked to aberrant activation of neural circuitry involved in emotion regulation (Beauregard, Paquette, & Lévesque, 2006; Etkin & Schatzberg, 2011). In recent years, technological advances in neuroimaging methods coupled with developments in machine learning have allowed for the non-invasive measurement and prediction of brain states in real-time, which can be used to provide feedback to facilitate regulation of brain states (LaConte, 2011). Real-time functional magnetic resonance imaging (rt-fMRI)-guided neurofeedback, has promise as a novel therapeutic method in which individuals are provided with tailored feedback to improve regulation of emotional responses (Stoeckel et al., 2014). However, effective use of this technology for such purposes likely entails the development of (a) a normative model of emotion processing to provide feedback for individuals with emotion processing difficulties; and (b) best practices concerning how these types of group models are designed and translated for use in a rt-fMRI environment (Ruiz, Buyukturkoglu, Rana, Birbaumer, & Sitaram, 2014). To this end, the present study utilized fMRI data from a standard emotion elicitation paradigm to examine the impact of several design decisions made during the development of a whole-brain model of affective processing. Using support vector machine (SVM) learning, we developed a group model that reliably classified brain states associated with passive viewing of positive, negative, and neutral images. After validating the group whole-brain model, we adapted this model for use in an rt-fMRI experiment, and using a second imaging dataset along with our group model, we simulated rt-fMRI predictions and tested options for providing feedback. / Master of Science