Connectivity Analysis in EEG Data: A Tutorial Review of the State of the Art and Emerging Trends

Understanding how different areas of the human brain communicate with each other is a crucial issue in neuroscience. The concepts of structural, functional and effective connectivity have been widely exploited to describe the human connectome, consisting of brain networks, their structural connections and functional interactions. Despite high-spatial-resolution imaging techniques such as functional magnetic resonance imaging (fMRI) being widely used to map this complex network of multiple interactions, electroencephalographic (EEG) recordings claim high temporal resolution and are thus perfectly suitable to describe either spatially distributed and temporally dynamic patterns of neural activation and connectivity. In this work, we provide a technical account and a categorization of the most-used data-driven approaches to assess brain-functional connectivity, intended as the study of the statistical dependencies between the recorded EEG signals. Different pairwise and multivariate, as well as directed and non-directed connectivity metrics are discussed with a pros-cons approach, in the time, frequency, and information-theoretic domains. The establishment of conceptual and mathematical relationships between metrics from these three frameworks, and the discussion of novel methodological approaches, will allow the reader to go deep into the problem of inferring functional connectivity in complex networks. Furthermore, emerging trends for the description of extended forms of connectivity (e.g., high-order interactions) are also discussed, along with graph-theory tools exploring the topological properties of the network of connections provided by the proposed metrics. Applications to EEG data are reviewed. In addition, the importance of source localization, and the impacts of signal acquisition and pre-processing techniques (e.g., filtering, source localization, and artifact rejection) on the connectivity estimates are recognized and discussed. By going through this review, the reader could delve deeply into the entire process of EEG pre-processing and analysis for the study of brain functional connectivity and learning, thereby exploiting novel methodologies and approaches to the problem of inferring connectivity within complex networks

Swayed by sound: sonic guidance as a neurorehabilitation strategy in the cerebellar ataxias

Cerebellar disease leads to problems in controlling movement. The most common difficulties are dysmetria and instability when standing. Recent understanding of cerebellar function has expanded to include non -motor aspects such as emotional, cognitive and sensory processing. Deficits in the acquisition and processing of sensory information are one explanation for the movement problems observed in cerebellar ataxia. Sensory deficits result in an inability to make predictions about future events; a primary function of the cerebellum. A question therefore, is whether augmenting or replacing sensory information can improve motor performance in cerebellar disease. This question is tested in this thesis by augmenting sensory information through the provision of an auditory movement guide.A variable described in motor control theory (tau) was used to develop auditory guides that were continuous and dynamic. A reaching experiment using healthy individuals showed that the timing of peak velocity, audiomotor coordination accuracy, and velocity of approach, could be altered in line with the movement parameters embedded in the auditory guides. The thesis then investigated the use of these sonic guides in a clinical population with cerebellar disease. Performance on neurorehabilitation exercises for balance control was tested in twenty people with cerebellar atrophy, with and without auditory guides. Results suggested that continuous, predictive, dynamic auditory guidance is an effective way of improving iii movement smoothness in ataxia (as measured by jerk). In addition, generating and swaying with imaginary auditory guides was also found to increase movement smoothness in cerebellar disease.Following the tests of instantaneous effects, the thesis then investigated the longterm consequences on motor behaviour of following a two -month exercise with auditory guide programme. Seven people with cerebellar atrophy were assessed pre - and post -intervention using two measures, weight -shifting and walking. The results of the weight -shifting test indicated that the sonic -guide exercise programme does not initiate long -term changes in motor behaviour. Whilst there were minor, improvements in walking, because of the weight -shifting results, these could not be attributed to the sonic guides. This finding confirms the difficulties of motor rehabilitation in people with cerebellar disease.This thesis contributes original findings to the field of neurorehabilitation by first showing that on -going and predictive stimuli are an appropriate tool for improving motor behaviour. In addition, the thesis is the first of its kind to apply externally presented guides that convey continuous meaningful information within a clinical population. Finally, findings show that sensory augmentation using the auditory domain is an effective way of improving motor coordination in some forms of cerebellar disease