Mental states monitoring through passive Brain-Computer Interface systems

The monitoring of cognitive functions aims at gaining information about the current cognitive state of the user by decoding brain signals. In recent years, this approach allowed to acquire valuable information about the cognitive aspects regarding the interaction of humans with external world. From this consideration, researchers started to consider passive application of brain–computer interface (BCI) in order to provide a novel input modality for technical systems solely based on brain activity. The objective of this thesis is to demonstrate how the passive Brain Computer Interfaces (BCIs) applications can be used to assess the mental states of the users, in order to improve the human machine interaction. Two main studies has been proposed. The first one allows to investigate whatever the Event Related Potentials (ERPs) morphological variations can be used to predict the users’ mental states (e.g. attentional resources, mental workload) during different reactive BCI tasks (e.g. P300-based BCIs), and if these information can predict the subjects’ performance in performing the tasks. In the second study, a passive BCI system able to online estimate the mental workload of the user by relying on the combination of the EEG and the ECG biosignals has been proposed. The latter study has been performed by simulating an operative scenario, in which the occurrence of errors or lack of performance could have significant consequences. The results showed that the proposed system is able to estimate online the mental workload of the subjects discriminating three different difficulty level of the tasks ensuring a high reliability.

Oscillatory mechanisms of conscious perception and attention

Although the prominent role of neural oscillations in perception and cognition has been continuously investigated, some critical questions remain unanswered. My PhD thesis was aimed at addressing some of them. First, can we dissociate oscillatory underpinnings of perceptual accuracy and subjective awareness? Current work would strongly suggest that this dissociation can be drawn. While the fluctuations in alpha-amplitude decide perceptual bias and metacognitive abilities, the speed of alpha activity (i.e., alpha-frequency) dictates sensory sampling, shaping perceptual accuracy. Second, how are these oscillatory mechanisms integrated during attention? The obtained results indicate that a top-down visuospatial mechanism modulates neural assemblies in visual areas via oscillatory re-alignment and coherence in the alpha/beta range within the fronto-parietal brain network. These perceptual predictions are reflected in the retinotopically distributed posterior alpha-amplitude, while perceptual accuracy is explained by the higher alpha-frequency at the to-be-attended location. Finally, sensory input, elaborated via fast gamma oscillations, is linked to specific phases of this slower activity via oscillatory nesting, enabling integration of the feedback-modulated oscillatory activity with sensory information. Third, how can we relate this oscillatory activity to other neural markers of behaviour (i.e., event-related potentials)? The obtained results favour the oscillatory model of ERP genesis, where alpha-frequency shapes the latency of early evoked-potentials, namely P1, with both neural indices being related to perceptual accuracy. On the other hand, alpha-amplitude dictates the amplitude of later P3 evoked-response, whereas both indices shape subjective awareness. Crucially, by combining different methodological approaches, including neurostimulation (TMS) and neuroimaging (EEG), current work identified these oscillatory-behavior links as causal and not just as co-occurring events. Current work aimed at ameliorating the use of the TMS-EEG approach by explaining inter-individual differences in the stimulation outcomes, which could be proven crucial in the way we design entrainment experiments and interpret the results in both research and clinical settings.

Analysis of cerebral and autonomic response to respiratory events in patients with Sleep Apnea Syndrome

The arousal scoring in Obstructive Sleep Apnea Syndrome (OSAS) is important to clarify the impact of the disease on sleep but the currently applied American Academy of Sleep Medicine (AASM) definition may underestimate the subtle alterations of sleep. The aims of the present study were to evaluate the impact of respiratory events on cortical and autonomic arousal response and to quantify the additional value of cyclic alternating pattern (CAP) and pulse wave amplitude (PWA) for a more accurate detection of respiratory events and sleep alterations in OSAS patients. A retrospective revision of 19 polysomnographic recordings of OSAS patients was carried out. Analysis was focused on quantification of apneas (AP), hypopneas (H) and flow limitation (FL) events, and on investigation of cerebral and autonomic activity. Only 41.1% of FL events analyzed in non rapid eye movement met the AASM rules for the definition of respiratory event-related arousal (RERA), while 75.5% of FL events ended with a CAP A phase. The dual response (EEG-PWA) was the most frequent response for all subtypes of respiratory event with a progressive reduction from AP to H and FL. 87.7% of respiratory events with EEG activation showed also a PWA drop and 53,4% of the respiratory events without EEG activation presented a PWA drop. The relationship between the respiratory events and the arousal response is more complex than that suggested by the international classification. In the estimation of the response to respiratory events, the CAP scoring and PWA analysis can offer more extensive information compared to the AASM rules. Our data confirm also that the application of PWA scoring improves the detection of respiratory events and could reduce the underestimation of OSAS severity compared to AASM arousal.

Distraction by task-irrelevant stimuli: the effects of endogenous spatial attention and visual working memory load

Salient stimuli, like sudden changes in the environment or emotional stimuli, generate a priority signal that captures attention even if they are task-irrelevant. However, to achieve goal-driven behavior, we need to ignore them and to avoid being distracted. It is generally agreed that top-down factors can help us to filter out distractors. A fundamental question is how and at which stage of processing the rejection of distractors is achieved. Two circumstances under which the allocation of attention to distractors is supposed to be prevented are represented by the case in which distractors occur at an unattended location (as determined by the deployment of endogenous spatial attention) and when the amount of visual working memory resources is reduced by an ongoing task. The present thesis is focused on the impact of these factors on three sources of distraction, namely auditory and visual onsets (Experiments 1 and 2, respectively) and pleasant scenes (Experiment 3). In the first two studies we recorded neural correlates of distractor processing (i.e., Event-Related Potentials), whereas in the last study we used interference effects on behavior (i.e., a slowing down of response times on a simultaneous task) to index distraction. Endogenous spatial attention reduced distraction by auditory stimuli and eliminated distraction by visual onsets. Differently, visual working memory load only affected the processing of visual onsets. Emotional interference persisted even when scenes occurred always at unattended locations and when visual working memory was loaded. Altogether, these findings indicate that the ability to detect the location of salient task-irrelevant sounds and identify the affective significance of natural scenes is preserved even when the amount of visual working memory resources is reduced by an ongoing task and when endogenous attention is elsewhere directed. However, these results also indicate that the processing of auditory and visual distractors is not entirely automatic.

Variability analysis of discrete event series and wavefront patterns in surface electrocardiogram: contributions to psychophysiological and clinical research

The surface electrocardiogram (ECG) is an established diagnostic tool for the detection of abnormalities in the electrical activity of the heart. The interest of the ECG, however, extends beyond the diagnostic purpose. In recent years, studies in cognitive psychophysiology have related heart rate variability (HRV) to memory performance and mental workload. The aim of this thesis was to analyze the variability of surface ECG derived rhythms, at two different time scales: the discrete-event time scale, typical of beat-related features (Objective I), and the “continuous” time scale of separated sources in the ECG (Objective II), in selected scenarios relevant to psychophysiological and clinical research, respectively. Objective I) Joint time-frequency and non-linear analysis of HRV was carried out, with the goal of assessing psychophysiological workload (PPW) in response to working memory engaging tasks. Results from fourteen healthy young subjects suggest the potential use of the proposed indices in discriminating PPW levels in response to varying memory-search task difficulty. Objective II) A novel source-cancellation method based on morphology clustering was proposed for the estimation of the atrial wavefront in atrial fibrillation (AF) from body surface potential maps. Strong direct correlation between spectral concentration (SC) of atrial wavefront and temporal variability of the spectral distribution was shown in persistent AF patients, suggesting that with higher SC, shorter observation time is required to collect spectral distribution, from which the fibrillatory rate is estimated. This could be time and cost effective in clinical decision-making. The results held for reduced leads sets, suggesting that a simplified setup could also be considered, further reducing the costs. In designing the methods of this thesis, an online signal processing approach was kept, with the goal of contributing to real-world applicability. An algorithm for automatic assessment of ambulatory ECG quality, and an automatic ECG delineation algorithm were designed and validated.

Identification of potential miRNAs related to classification and treatment response of actinic keratosis

The Workflow activity was the following: Preliminary phase: Identification of 18 Formalin-fixed paraffin embedded (FFPE) samples (9 patients) («matched» 9 AK lesions and 9 SCC lesions). Working on biopsies samples we perform an extraction and RNA analysis with droplet Digital PCR (ddPCR) and we perform the data analysis. Second and final step phase: Evaluation of additional 39 subjects (36 men and 3 women). Results: We perform an evaluation and comparison of the following miRNA: miR-320 (a miRNA involved in apoptosis and cell proliferation control; miR-204, a miRNA involved in cell proliferation in and miRNA-16-5p, a miRNA involved in apoptosis).Conclusion: Our data suggest that there is no significant variation in the expression of the three tested microRNAs between adjacent AK lesions and squamous-cell carcinoma. However, a relevant trend has been observed Furthermore, by evaluating the miRNA expression trend between keratosis and carcinoma of the same patient, it is observed that there is no "uniform trend": for some samples the expression rises for the transition from AK to SCC and viceversa.