Investigating the effects of neuromodulatory training on autistic traits: a multi-methods psychophysiological study.

Autism spectrum disorder (ASD) is characterized by noticeable difficulties with social interaction and communication. Building on past research in this area and with the aim of improving methodological perspectives, a multi method approach to the study of ASD, mirror neurons and neurofeedback was taken. This thesis is made up of three main experiments: 1) A descriptive study of the resting state electroencephalography (EEG) across the spectrum of autistic traits in neurotypical individuals, 2) A comparison of 3 EEG protocols on MNs activation (mu suppression) and its difference according to self-reported traits of autism in neurotypical individuals, and 3) Neurofeedback training (NFT) on individuals with high autistic traits. In chapters 3 and 4 we employed simultaneous monitoring of physiological data. For chapter 3 EEG and eye-tracking was used, In the case of chapter 4, EEG and eye-tracking as well functional near infrared spectroscopy (fNIRS). Overall the findings revealed differences in mu rhythm reactivity associated to AQ traits. In chapter 2, the rEEG showed that individuals with high AQ scores showed less activation of frontal and fronto-central regions combined with higher levels of complexity in fronto-temporal, temporal, parietal and parieto-occipital areas. In chapter 3, EEG protocols that elicited Mu reactivity in individuals with different AQ traits suggested that as the AQ traits become more pronounced in neurotypical population, the event-related desynchronization (ERD) in low alpha declines. Chapter 3 was also the basis for the choice of pre/post assessment for chapter 4. In chapter 4 the multi-method physiological approach provided parallel physiological evidence for the effects of NFT in sensorimotor reactivity, namely, an increase in ERD in high alpha, higher levels of oxygenated haemoglobin and changes to the amplitude and frequency in the microstructure of mu for participants who underwent active training as opposed to a sham group

Multimodal autoencoder predicts fNIRS resting state from EEG signals

In this work, we introduce a deep learning architecture for evaluation on multimodal electroencephalographic (EEG) and functional near-infrared spectroscopy (fNIRS) recordings from 40 epileptic patients. Long short-term memory units and convolutional neural networks are integrated within a multimodal sequence-to-sequence autoencoder. The trained neural network predicts fNIRS signals from EEG, sans a priori, by hierarchically extracting deep features from EEG full spectra and specific EEG frequency bands. Results show that higher frequency EEG ranges are predictive of fNIRS signals with the gamma band inputs dominating fNIRS prediction as compared to other frequency envelopes. Seed based functional connectivity validates similar patterns between experimental fNIRS and our model’s fNIRS reconstructions. This is the first study that shows it is possible to predict brain hemodynamics (fNIRS) from encoded neural data (EEG) in the resting human epileptic brain based on power spectrum amplitude modulation of frequency oscillations in the context of specific hypotheses about how EEG frequency bands decode fNIRS signals

Cognitive Assessment and Rehabilitation of subjects with Traumatic Brain Injury

This thesis regards the study and the development of new cognitive assessment and rehabilitation techniques of subjects with traumatic brain injury (TBI). In particular, this thesis i) provides an overview about the state of art of this new assessment and rehabilitation technologies, ii) suggests new methods for the assessment and rehabilitation and iii) contributes to the explanation of the neurophysiological mechanism that is involved in a rehabilitation treatment. Some chapters provide useful information to contextualize TBI and its outcome; they describe the methods used for its assessment/rehabilitation. The other chapters illustrate a series of experimental studies conducted in healthy subjects and TBI patients that suggest new approaches to assessment and rehabilitation. The new proposed approaches have in common the use of electroencefalografy (EEG). EEG was used in all the experimental studies with a different purpose, such as diagnostic tool, signal to command a BCI-system, outcome measure to evaluate the effects of a treatment, etc. The main achieved results are about: i) the study and the development of a system for the communication with patients with disorders of consciousness. It was possible to identify a paradigm of reliable activation during two imagery task using EEG signal or EEG and NIRS signal; ii) the study of the effects of a neuromodulation technique (tDCS) on EEG pattern. This topic is of great importance and interest. The emerged founding showed that the tDCS can manipulate the cortical network activity and through the research of optimal stimulation parameters, it is possible move the working point of a neural network and bring it in a condition of maximum learning. In this way could be possible improved the performance of a BCI system or to improve the efficacy of a rehabilitation treatment, like neurofeedback

Existence of Initial Dip for BCI: An Illusion or Reality

A tight coupling between the neuronal activity and the cerebral blood flow (CBF) is the motivation of many hemodynamic response (HR)-based neuroimaging modalities. The increase in neuronal activity causes the increase in CBF that is indirectly measured by HR modalities. Upon functional stimulation, the HR is mainly categorized in three durations: (i) initial dip, (ii) conventional HR (i.e., positive increase in HR caused by an increase in the CBF), and (iii) undershoot. The initial dip is a change in oxygenation prior to any subsequent increase in CBF and spatially more specific to the site of neuronal activity. Despite additional evidence from various HR modalities on the presence of initial dip in human and animal species (i.e., cat, rat, and monkey); the existence/occurrence of an initial dip in HR is still under debate. This article reviews the existence and elusive nature of the initial dip duration of HR in intrinsic signal optical imaging (ISOI), functional magnetic resonance imaging (fMRI), and functional near-infrared spectroscopy (fNIRS). The advent of initial dip and its elusiveness factors in ISOI and fMRI studies are briefly discussed. Furthermore, the detection of initial dip and its role in brain-computer interface using fNIRS is examined in detail. The best possible application for the initial dip utilization and its future implications using fNIRS are provided

Neurofeedback Therapy for Enhancing Visual Attention: State-of-the-Art and Challenges

We have witnessed a rapid development of brain-computer interfaces (BCIs) linking the brain to external devices. BCIs can be utilized to treat neurological conditions and even to augment brain functions. BCIs offer a promising treatment for mental disorders, including disorders of attention. Here we review the current state of the art and challenges of attention-based BCIs, with a focus on visual attention. Attention-based BCIs utilize electroencephalograms (EEGs) or other recording techniques to generate neurofeedback, which patients use to improve their attention, a complex cognitive function. Although progress has been made in the studies of neural mechanisms of attention, extraction of attention-related neural signals needed for BCI operations is a difficult problem. To attain good BCI performance, it is important to select the features of neural activity that represent attentional signals. BCI decoding of attention-related activity may be hindered by the presence of different neural signals. Therefore, BCI accuracy can be improved by signal processing algorithms that dissociate signals of interest from irrelevant activities. Notwithstanding recent progress, optimal processing of attentional neural signals remains a fundamental challenge for the development of efficient therapies for disorders of attention

Near Infrared Spectroscopy and Electroencephalography For an Assessment of Brain Function in patients with Disorders of Consciousness

There is growing evidence that some of the patients presenting with the Vegetative State (VS), also known as Unresponsive Wakefulness State, can respond to environmental stimuli. This response can be detected by using functional brain imaging, including electroencephalography (EEG) or Near Infrared Spectroscopy (NIRS). By definition, the VS patients are awake but not aware, unlike the patients in the Minimally Conscious State (MCS), who have some fluctuating awareness. Since consciousness is impaired in both conditions, these states are also referred as Disorders of Consciousness (DOC) or prolonged Disorders of Consciousness (pDOC) This thesis aims to develop a bedside applicable tool using the EEG and NIRS for brain function assessment in VS and MCS patients. In this study, two experimental protocols have been developed and validated on healthy subjects. The results showed that using the motor imagery and own subject name stimuli, some of the VS patients were able to wilfully modulate their brain activity in response to those stimuli. The results presented in this thesis can be implemented as a part of a protocol for brain function assessment in pDOC patients and can be used for the further studies for better understanding of the brain function in these patients

A Multifaceted Approach to Covert Attention Brain-Computer Interfaces

Over the last years, brain-computer interfaces (BCIs) have shown their value for assistive technology and neurorehabilitation. Recently, a BCI-approach for the rehabilitation of hemispatial neglect has been proposed on the basis of covert visuospatial attention (CVSA). CVSA is an internal action which can be described as shifting one's attention to the visual periphery without moving the actual point of gaze. Such attention shifts induce a lateralization in parietooccipital blood flow and oscillations in the so-called alpha band (8-14 Hz), which can be detected via electroencephalography (EEG), magnetoencephalography (MEG) or functional magnetic resonance imaging (fMRI). Previous studies have proven the technical feasibility of using CVSA as a control signal for BCIs, but unfortunately, these BCIs could not provide every subject with sufficient control. The aim of this thesis was to investigate the possibility of amplifying the weak lateralization patterns in the alpha band - the main reason behind insufficient CVSA BCI performance. To this end, I have explored three different approaches that could lead to better performing and more inclusive CVSA BCI systems. The first approach illuminated the changes in the behavior and brain patterns by closing the loop between subject and system with continuous real-time feedback at the instructed locus of attention. I could observe that even short (20 minutes) stretches of real-time feedback have an effect on behavioral correlates of attention, even when the changes observed in the EEG remained less conclusive. The second approach attempted to complement the information extracted fromthe EEG signal with another sensing modality that could provide additional information about the state of CVSA. For this reason, I firstly combined functional functional near-infrared spectroscopy (fNIRS) with EEG measurements. The results showed that, while the EEG was able to pick up the expected lateralization in the alpha band, the fNIRS was not able to reliably image changes in blood circulation in the parietooccipital cortex. Secondly, I successfully combined data from the EEG with measures of pupil size changes, induced by a high illumination contrast between the covertly attended target regions, which resulted in an improved BCI decoding performance. The third approach examined the option of using noninvasive electrical brain stimulation to boost the power of the alpha band oscillations and therefore render the lateralization pattern in the alpha band more visible compared to the background activity. However, I could not observe any impact of the stimulation on the ongoing alpha band power, and thus results of the subsequent effect on the lateralization remain inconclusive. Overall, these studies helped to further understand CVSA and lay out a useful basis for further exploration of the connection between behavior and alpha power oscillations in CVSA tasks, as well as for potential directions to improve CVSA-based BCIs

Proceedings of the 3rd International Mobile Brain/Body Imaging Conference : Berlin, July 12th to July 14th 2018

The 3rd International Mobile Brain/Body Imaging (MoBI) conference in Berlin 2018 brought together researchers from various disciplines interested in understanding the human brain in its natural environment and during active behavior. MoBI is a new imaging modality, employing mobile brain imaging methods like the electroencephalogram (EEG) or near infrared spectroscopy (NIRS) synchronized to motion capture and other data streams to investigate brain activity while participants actively move in and interact with their environment. Mobile Brain / Body Imaging allows to investigate brain dynamics accompanying more natural cognitive and affective processes as it allows the human to interact with the environment without restriction regarding physical movement. Overcoming the movement restrictions of established imaging modalities like functional magnetic resonance tomography (MRI), MoBI can provide new insights into the human brain function in mobile participants. This imaging approach will lead to new insights into the brain functions underlying active behavior and the impact of behavior on brain dynamics and vice versa, it can be used for the development of more robust human-machine interfaces as well as state assessment in mobile humans.DFG, GR2627/10-1, 3rd International MoBI Conference 201

Social and Affective Neuroscience of Everyday Human Interaction

This Open Access book presents the current state of the art knowledge on social and affective neuroscience based on empirical findings. This volume is divided into several sections first guiding the reader through important theoretical topics within affective neuroscience, social neuroscience and moral emotions, and clinical neuroscience. Each chapter addresses everyday social interactions and various aspects of social interactions from a different angle taking the reader on a diverse journey. The last section of the book is of methodological nature. Basic information is presented for the reader to learn about common methodologies used in neuroscience alongside advanced input to deepen the understanding and usability of these methods in social and affective neuroscience for more experienced readers

Neuroimaging of human motor control in real world scenarios: from lab to urban environment

The main goal of this research programme was to explore the neurophysiological correlates of human motor control in real-world scenarios and define mechanism-specific markers that could eventually be employed as targets of novel neurorehabilitation practice. As a result of recent developments in mobile technologies it is now possible to observe subjects' behaviour and monitor neurophysiological activity whilst they perform natural activities freely. Investigations in real-world scenarios would shed new light on mechanisms of human motor control previously not observed in laboratory settings and how they could be exploited to improve rehabilitative interventions for the neurologically impaired. This research programme was focussed on identifying cortical mechanisms involved in both upper- (i.e. reaching) and lower-limb (i.e. locomotion) motor control. Complementary results were obtained by the simultaneous recordings of kinematic, electromyographic and electrocorticographic signals. To study motor control of the upper-limb, a lab­based setup was developed, and the reaching movement of healthy young individuals was observed in both stable and unstable (i.e. external perturbation) situations. Robot-mediated force-field adaptation has the potential to be employed in rehabilitation practice to promote new skills learning and motor recovery. The muscular (i.e. intermuscular couplings) and neural (i.e. spontaneous oscillations and cortico­muscular couplings) indicators of the undergoing adaptation process were all symbolic of adaptive strategies employed during early stages of adaptation. The medial frontal, premotor and supplementary motor regions appeared to be the principal cortical regions promoting adaptive control and force modulation. To study locomotion control, a mobile setup was developed and daily life human activities (i.e. walking while conversing, walking while texting with a smartphone) were investigated outside the lab. Walking in hazardous environments or when simultaneously performing a secondary task has been demonstrated to be challenging for the neurologically impaired. Healthy young adults showed a reduced motor performance when walking in multitasking conditions, during which whole-brain and task-specific neural correlates were observed. Interestingly, the activity of the left posterior parietal cortex was predictive of the level of gait stability across individuals, suggesting a crucial role of this area in gait control and determination of subject specific motor capabilities. In summary, this research programme provided evidence on different cortical mechanisms operative during two specific scenarios for "real­world" motor behaviour in and outside the laboratory-setting in healthy subjects. The results suggested that identification of neuro-muscular indicators of specific motor control mechanisms could be exploited in future "real-world" rehabilitative practice