Using tDCS to improve speech processes in typical speakers and people who stutter

Stuttering is a speech disorder for which treatment options are limited. Brain stimulation methods such as tDCS used as an adjunct to treatments enhance positive effects of intervention. This thesis addressed whether tDCS applied to the left inferior frontal gyrus would improve speech processes in typical speakers (TS) and people who stutter (PWS). Study 1.1 with TS showed that tDCS resulted in enhanced performance (reduction in speech reaction times) for three, but not one, syllable words in a picture naming task. Such interaction between stimuli complexity and tDCS was explored in Study 1.2. A picturenaming task was used with three syllable stimuli. Primes either facilitated the speech plan (low complexity) or required speech-plan reformulation. When anodal tDCS was applied, incongruent trials alone were significantly quicker than sham trials, replicating the effect of difficulty. Study 3 with TS applied tDCS whilst participants repeated tongue twisters. Anodal tDCS resulted in significantly faster tongue twister completion times compared to sham or cathodal stimulation. The studies with TS indicated that tDCS improves speech processes, particularly when task complexity is high. Study 4, applied tDCS to PWS alongside a challenging intervention known to reduce stuttering. There were reductions in stuttering during conversation that trended towards significance (sample size was small). Finally, we examined inferior frontal gyrus neural activity in PWS and TS whilst conversing socially or to a recording. The left inferior frontal gyrus showed significant and unique responses during face-to-face conversation compared to audio conversation. Findings indicated that the left inferior frontal gyrus is differentially involved when PWS communicate in different styles. This thesis demonstrated that tDCS is a promising adjunct for improving speech production processes in TS and PWS to use with challenging tasks and interventions. Further research is required to understand mechanisms of effect and to further refine effects for this promising approach

Multi-sensory working memory - in vision, audition and touch

Our nervous systems can perform a vast variety of cognitive tasks, many involving several different senses. Although sensory systems provide a basis for the creation of mental representations, we rely on memory to form mental representations of information that is no longer present in our external world. Focussing on the initial stage of this process, working memory (WM), where information is retained actively over a short time course, experiments included in this thesis were directed toward understanding the nature of sensory representations across the senses (vision, audition and touch). Instead of quantifying how many items one can hold in each sensory modality (all-or-none representations), new response methods were devised to capture the qualitative nature of sensory representations. Measuring quality rather than quantity of information held in WM, has led to the re-evaluation of the nature of its underlying capacity limits. Rather than assuming that WM capacity is limited to a fixed number of items, it may be more suitable to describe WM as a resource which can be shared and flexibly distributed across sensory information. Thus it has been proposed that at low loads we can hold information at a high resolution. However, as soon as memory load is increased, there is a deterioration of the quality at which each individual item can be represented in WM. The resource model of WM has been applied to describe processes of visual WM, but has not been investigated for other sensory modalities. In the first part of my thesis I demonstrate behaviourally that the resource model can be extended to account for processes in auditory WM, associated with the storage of sound frequency (pitch, chapter 2) and speech sounds (phonemes, chapter 3). I then show that it can also be extended to account for storage of tactile vibrational frequencies (chapter 4). Overall, the results suggest that memory representations become noisier with an increase in information load, consistent with the concept that representations are coded as distributed patterns. A pattern may code for individual object features or entire objects. As studies in chapter 2 - 4 only looked at a single type of feature each in separation, I next examined WM information storage for auditory objects, composed of multiple features (chapter 5). Object formation involves binding of features, which become reorganized to create more complex unified representations of previously distributed information. The results revealed a clear feature extraction cost when recall was tested on individual features rather than on integrated objects. One interpretation of these findings is that, at some level in the auditory system, sounds may be stored as integrated objects. In a final study, using fMRI with MVPA (mulitvoxel pattern analysis), memory traces represented as distributed patterns of brain activity were decoded from different regions of the auditory system (chapter 6). The major goal was to resolve the debate on the role of early sensory cortices in cognition: are they primarily involved in the perception of low-level stimulus features or also in maintenance of the same features in memory? I demonstrate that perception and memory share common neural substrates, where early auditory cortex serves as a substrate to accommodate both processes. Overall, in this thesis memory representations were characterized across the senses in three different ways: (1) measuring them in terms of their quality or resolution, (2) testing whether the preferred format is on the feature or integrated object level; and (3) as patterns of brain activity. Findings converge along the concept that noisy representations actively held in WM are coded as distributed patterns in the brain

Change blindness: eradication of gestalt strategies

Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task

Top-down amplification of predicted visual input behind a frosted occluder

This thesis is comprised of five chapters. It includes two experimental chapters in which I detail both psychophysical and fMRI studies carried out at the University of Glasgow as part of this PhD project. These are followed by a literature review which outlines the implementation of ultra-high-resolution fMRI, both generally within the field and within a specific project proposal. Chapter 1 is a general introduction. I outline the broad organisation and basic functions of the visual system at the pre-cortical and cortical stages, in turn. I then discuss the concept of feedback within the visual system, outlining what feedback is, what it does and how it is implemented before outlining the rationale for the thesis. Chapter 2 is an experimental chapter detailing a series of psychophysical experiments. These experiments employ a partial occlusion paradigm to explore how top-down predicted information can influence the processing of degraded feedforward input. Throughout the experimental series, different aspects of this question are addressed in order to investigate whether the consistency of contextual information influences the detection and/or recognition of low-contrast visual scenes. Chapter 3 is another experimental chapter which details two 3T fMRI experiments. These projects also employed a partial occlusion paradigm to investigate contextual modulation on the processing of degraded feedforward input at the neuronal level in early visual cortex. Both univariate and multivariate analysis techniques were used to reveal the impact of consistency within top-down information. Chapter 4 contains a literature review which looks into ultra-high-resolution fMRI. Here, I detail the motivation behind the development of higher resolution imaging as well as potential confounds and limitations. I also outline adaptations required at higher resolution in terms of data acquisition and analysis as well as briefly exploring layer-specific findings within the visual cortex. Finally, I propose a 7T fMRI project that would continue to explore the influence of top-down predictions on the processing of degraded visual input by expanding the investigation to a laminar level. Chapter 5 is a general discussion which summarises the key points from each of the previous chapters and briefly discusses their conceptual relation to the current field and beyond

Action control in uncertain environments

A long-standing dichotomy in neuroscience pits automatic or reflexive drivers of behaviour against deliberate or reflective processes. In this thesis I explore how this concept applies to two stages of action control: decision-making and response inhibition. The first part of this thesis examines the decision-making process itself during which actions need to be selected that maximise rewards. Decisions arise through influences from model-free stimulus-response associations as well as model-based, goal-directed thought. Using a task that quantifies their respective contributions, I describe three studies that manipulate the balance of control between these two systems. I find that a pharmacological manipulation with levodopa increases model-based control without affecting model-free function; disruption of dorsolateral prefrontal cortex via magnetic stimulation disrupts model-based control; and direct current stimulation to the same prefrontal region has no effect on decision-making. I then examine how the intricate anatomy of frontostriatal circuits subserves reinforcement learning using functional, structural and diffusion magnetic resonance imaging (MRI). A second stage of action control discussed in this thesis is post-decision monitoring and adjustment of action. Specifically, I develop a response inhibition task that dissociates reactive, bottom-up inhibitory control from proactive, top-down forms of inhibition. Using functional MRI I show that, unlike the strong neural segregation in decision-making systems, neural mechanisms of reactive and proactive response inhibition overlap to a great extent in their frontostriatal circuitry. This leads to the hypothesis that neural decline, for 4 example in the context of ageing, might affect reactive and proactive control similarly. I test this in a large population study administered through a smartphone app. This shows that, against my prediction, reactive control reliably declines with age but proactive control shows no such decline. Furthermore, in line with data on gender differences in age-related neural degradation, reactive control in men declines faster with age than that of women

Task-based fMRI investigation of the newborn brain: sensorimotor development and learning

Human brain development relies upon the interaction between genetic and environmental factors, and the latter plays a critical role during the perinatal period. In this period, neuronal plasticity through experience-dependent activity is enhanced in the sensory systems, and drive the maturation of the brain. While plasticity is essential for maturation, it is also a source of vulnerability as altered early experiences may interact with the normal course of development. This is particularly evident in infants born preterm, who are prematurely exposed to a sensory-rich environment, and at risk or neurodevelopmental disorders. In keeping with the somatosensory system being at a critical period for development during late gestation, sensorimotor disorders, such as cerebral palsy, are more common in preterm compared with full-term born infants. It is therefore important to understand the normal trajectory of sensorimotor development and how this may be moulded by early sensory experiences. It is well acknowledged that the sensorimotor cortex is topographically organised so that different body parts map to a specific location within the cortex and this map is generally referred to as the ``homunculus". Although the somatotopy has been well characterised in the mature brain, it remains unknown when this organisation emerges during development. Animal studies hints that functional cortical maps might emerge across the equivalent period to the third trimester of human gestation, nevertheless there is currently no evidence. Therefore, I first investigated the topography of the preterm somatosensory cortex in a group of newborn infants. In this purpose I used fMRI and automated robotic tools and measured the functional responses to different sensory simulations (delivered to the mouth, wrists and ankles). The results provide evidence that it is possible to identify distinct areas in the somatosensory cortex devoted to different body parts even in the preterm brain supporting the presence of an immature \textit{homunculus}. Next, I wanted to investigate how activity and development in the sensorimotor system are influenced by experience. Experience-dependent plasticity is the basis of learning (e.g. adaptive behaviour), which is observed in newborn infants. Associative learning in particular has been widely investigated in infants, however, the underlining neuronal processes have previously been poorly understood. To study the neural correlates of associative learning in newborn infants, I developed and used a classical conditioning paradigm in combination with robot-assisted fMRI. The results confirm that associative learning can occur even at this early stage of life and with non-aversive stimuli. More importantly, I could observe learning-induced changes in brain activity within the primary sensory cortices, suggesting that such experience can shape cortical circuitry and is likely to influence early brain development.Open Acces

Quantitative Multimodal Mapping Of Seizure Networks In Drug-Resistant Epilepsy

Over 15 million people worldwide suffer from localization-related drug-resistant epilepsy. These patients are candidates for targeted surgical therapies such as surgical resection, laser thermal ablation, and neurostimulation. While seizure localization is needed prior to surgical intervention, this process is challenging, invasive, and often inconclusive. In this work, I aim to exploit the power of multimodal high-resolution imaging and intracranial electroencephalography (iEEG) data to map seizure networks in drug-resistant epilepsy patients, with a focus on minimizing invasiveness. Given compelling evidence that epilepsy is a disease of distorted brain networks as opposed to well-defined focal lesions, I employ a graph-theoretical approach to map structural and functional brain networks and identify putative targets for removal. The first section focuses on mesial temporal lobe epilepsy (TLE), the most common type of localization-related epilepsy. Using high-resolution structural and functional 7T MRI, I demonstrate that noninvasive neuroimaging-based network properties within the medial temporal lobe can serve as useful biomarkers for TLE cases in which conventional imaging and volumetric analysis are insufficient. The second section expands to all forms of localization-related epilepsy. Using iEEG recordings, I provide a framework for the utility of interictal network synchrony in identifying candidate resection zones, with the goal of reducing the need for prolonged invasive implants. In the third section, I generate a pipeline for integrated analysis of iEEG and MRI networks, paving the way for future large-scale studies that can effectively harness synergy between different modalities. This multimodal approach has the potential to provide fundamental insights into the pathology of an epileptic brain, robustly identify areas of seizure onset and spread, and ultimately inform clinical decision making