Stochastic Resonance Reduces Sway and Gait Variability in Individuals With Unilateral Transtibial Amputation: A Pilot Study

Sub-threshold (imperceptible) vibration, applied to parts of the body, impacts how people move and perceive our world. Could this idea help someone who has lost part of their limb? Sub-threshold vibration was applied to the thigh of the affected limb of 20 people with unilateral transtibial amputation. Vibration conditions tested included two noise structures: pink and white. Center of pressure (COP) excursion (range and root-mean-square displacements) during quiet standing, and speed and spatial stride measures (mean and standard deviations of step length and width) during walking were assessed. Pink noise vibration decreased COP displacements in standing, and white noise vibration decreased sound limb step length standard deviation in walking. Sub-threshold vibration positively impacted aspects of both posture and gait; however, different noise structures had different effects. The current study represents foundational work in understanding the potential benefits of incorporating stochastic resonance as an intervention for individuals with amputation

Midfrontal theta tracks action monitoring over multiple interactive time scales

Contains fulltext : 161849pub.pdf (publisher's version ) (Open Access)Quickly detecting and correcting mistakes is a crucial brain function. EEG studies have identified an idiosyncratic electrophysiological signature of online error correction, termed midfrontal theta. Midfrontal theta has so far been investigated over the fast time-scale of a few hundred milliseconds. But several aspects of behavior and brain activity unfold over multiple time scales, displaying "scale-free" dynamics that have been linked to criticality and optimal flexibility when responding to changing environmental demands. Here we used a novel line-tracking task to demonstrate that midfrontal theta is a transient yet non-phase-locked response that is modulated by task performance over at least three time scales: a few hundred milliseconds at the onset of a mistake, task performance over a fixed window of the previous 5s, and scale-free-like fluctuations over many tens of seconds. These findings provide novel evidence for a role of midfrontal theta in online behavioral adaptation, and suggest new approaches for linking EEG signatures of human executive functioning to its neurobiological underpinnings

Are There Brain-Based Predictors of the Ability to Learn a New Skill in Healthy Ageing and Can They Help in the Design of Effective Therapy after Stroke?

This thesis aimed at looking for neural correlates of motor adaptation as a model of rehabilitation after brain injury. Healthy adults across the lifespan and stroke patients were tested in a force-field learning paradigm. This thesis focuses on EEG analysis and the complex relationship of brain-derived measures with observed behaviour. To describe each domain in detail, the focus was first on finding group differences between older and younger healthy adults in a similar manner as it was later between stroke patients versus healthy controls. The analyses were finalised by looking for relationships between the EEG and motor performance data in a multiple linear regression approach. As candidate EEG biomarkers of motor adaptation, error related event related potential around movement onset in the frontocentral electrodes was chosen in time domain. In the time-frequency domain, the focus was on movement related beta band spectral perturbation, looking at the electrodes over the primary motor cortex and the frontocentral ROI found significant in the time domain. Finally, functional connectivity was analysed focusing first on electrode over the primary motor cortex contralateral to the movement as a seed region, to narrow down the analysis to bilateral motor cortex connectivity and connectivity between primary motor cortex contralateral to the movement and the frontocentral region identified as important in the time domain analysis. The crucial part of the project was analysing the relationship between the neural and kinematic measures. The most important predictor of summed error in motor adaptation was the connectivity between C3 and C4 electrode at the baseline prestimulus period in motor adaptation condition and pinch asymmetry. Higher prestimulus interhemispheric connectivity was associated with bigger deviation from the optimal trajectory. When looking at summed error dynamic derivative as a dependent variable - performance index - it was the ERP at the central error-related ROI that explained the most variance. It can be concluded that higher baseline interhemispheric connectivity can be a reflection of a maladaptive process, perhaps related to increased interhemispheric inhibition. It is important to also note that the same connectivity at different timepoints in the movement can be of different significance - differences between stroke patients and controls were present in the postmovement period. In conclusion, brain information could be helpful for e.g. stratifying patients into different intensity programs based on their predicted potential to recover. Moreover, brain information could be utilised to apply closed-loop systems modulating the intensity of tasks to reach the optimal brain state that facilitates learning. I believe this work will help incorporating brain-derived measures in informing neurorehabilitation programmes in the future

Spatiotemporal neural correlates of confidence in perceptual decision making

In our interactions with the environment, we often make inferences based on noisy or incomplete perceptual information - for example, judging whether the person waving their hand in the distance is someone we know (as opposed to a stranger, greeting the person behind us). Such judgments are accompanied by a sense of confidence, that is, a degree of belief that we are correct, which ultimately determines how we act, adjust our subsequent decisions, or learn from errors. Neuroscience has only recently begun to characterise the representations of confidence in the animal and human brain, however the neural mechanisms and network dynamics supporting these representations are still unclear. The current thesis presents empirical findings from three studies that sought to provide a more complete characterisation of confidence during perceptual decision making, using a combination of electrophysiological and neuroimaging methods. Specifically, Study 1 (Chapter 2) investigated the temporal characteristics of confidence in relation to the perceptual decision. We recorded EEG measurements from human subjects during performance of a face vs. car categorisation task. On some trials, subjects were offered the possibility to opt out of the choice in exchange for a smaller but certain reward (relative to the reward obtained for correct choices), and the choice to use or decline this option reflected subjects’ confidence in their perceptual judgment. Neural activity discriminating between high vs. low confidence trials could be observed peaking approximately 600 ms after stimulus onset. Importantly, the temporal profile of this activity resembled a ramp-like process of evidence accumulation towards a decision, with confidence being reflected in the rate of the accumulation. Our results are in line with the notion that neural representations of confidence may arise from the same process that supports decision formation. Extending on these findings, in Study 2 (Chapter 3) we asked whether rhythmic patterns within the EEG signals may offer additional insights into the neural representations of confidence. Using an exploratory analysis of data from Study 1, we identified confidence-discriminating oscillatory activity in the alpha and beta frequency bands. This was most prominent over the sensorimotor electrodes contralateral to the motor effector that subjects used to indicate choice (i.e., right hand), consistent with a motor preparatory signal. Importantly however, the effect was transient in nature, peaking long before subjects could execute a response, and thus ruling out a direct link with overt motor behaviour. More intriguingly, the observed confidence effect appeared to overlap in time with the non-oscillatory representation of confidence identified in Study 1. In line with the view that motor systems track the evolution of the perceptual decision in preparation for impending action, results from Studies 1 and 2 open the possibility that confidence-related information may also be contained within these signals. Finally, following on from our work in the first study, we next aimed to capitalise on the single-trial neural representations of confidence obtained with EEG, in order to identify potentially correlated activity with high spatial resolution. To this end, in Study 3 (Chapter 4) we recorded simultaneous EEG and fMRI data while subjects performed a speeded motion discrimination task and rated their confidence on a trial-by-trial basis. Analysis of the EEG revealed a confidence-discriminating neural component which appeared prior to participants’ overt choice and was spatiotemporally consistent with our results from the first study. Crucially, we showed that haemodynamic responses in the ventromedial prefrontal cortex (VMPFC) were uniquely explained by trial-to-trial fluctuations in these early confidence-related neural signals. Notably, this activation was additional to what could be explained by subjects’ confidence ratings alone. We speculated that the VMPFC may support an early and/or automatic readout of perceptual confidence, potentially preceding explicit metacognitive appraisal. Together, our results reveal novel insights into the neural representations of perceptual confidence in the human brain, and point to new research directions that may help further disentangle the neural dynamics supporting confidence and metacognition

Automatic visuospatial attention shifts: Perceptual correlates, interventions and oscillatory signatures

Our visual perception is shaped by both external and internal factors, which continuously compete for limited neural resources. Salient external (exogenous) events capture our attention automatically, whereas internal (endogenous) attention can be directed towards sensory events according to our current behavioural goals. Advances in neuroimaging and brain stimulation have allowed us to begin to map the underlying functional neural architecture mediating both exogenously driven and endogenously controlled visual attention, including electrophysiological techniques such as electroencephalography and magnetoencephalography (EEG/MEG). However, while the neural EEG/MEG correlates of endogenously controlled attention have been investigated in much detail, the neural EEG/MEG correlates of exogenously driven attention are substantially less well understood. One reason for this is that exogenously driven effects are difficult to isolate from the influence of endogenous control processes. In a series of three experiments, I sought to: 1) Study how the perceptual outcomes of both endogenously and exogenously driven attention can be effectively dissociated and investigated. 2) Provide a better understanding of the functional architecture of attention control in regards to its underlying neural substrates and oscillatory signatures, particularly when exogenously driven. To this end, I employed a visuospatial attention paradigm which, by design, behaviourally dissociates exogenous from endogenously driven effects (experiment 1). Furthermore, by utilizing the same behavioural paradigm in combination with neuronavigated MRI-based transcranial magnetic stimulation (TMS) over two key attentional network nodes (i.e., the right intraprarietal sulcus and right temporo-parietal junction), I probed the extent to which the neural substrates of endogenous vs. exogenous orienting are overlapping or can be dissociated (experiment 2). Lastly, I used electroencephalography (EEG) to investigate the oscillatory signatures underlying attention in a task which is typically employed to study exogenous orienting and which putatively triggers exogenous attention in isolation (experiment 3). The results revealed that while exogenous attentional processes can be behaviourally dissociated from endogenous attention (experiment 1), the neural substrates of exogenous attention appear to cover a wide network of attention areas. This includes nodes in both the right ventral attention network (i.e., right temporo-parietal junction) but also the right dorsal network (i.e., the right intraparietal sulcus), which has predominantly been associated with endogenous attention control (experiment 2). Interestingly, even in tasks that have been utilized to test exogenous attentional effects in isolation, endogenous control processes, as indexed by increased mid-frontal theta-band activity, can heavily influence the behavioural outcome (experiment 3). Based on these results, I conclude that there appears to be strong interplay between endogenous control and exogenously driven attention processes. These findings highlight that in order to better understand the functional architecture of (purely) exogenously driven effects, we need to effectively account for the potential influence of endogenous control. One approach to achieve this is by manipulating both types of attention simultaneously instead of in separation, as illustrated in the present work

Neural correlates of performance monitoring during discrete and continuous tasks

Monitoring our actions is a key function of the brain for adaptive and successful behavior. Actions can be discrete such as when pressing a button, or continuous, such as driving a car. Moreover, we evaluate our actions as correct or erroneous (performance monitoring) and this appraisal of performance comes with various levels of confidence (metacognition). However, studies of performance monitoring have focused on discrete actions and are mostly agnostic to metacognitive judgments. The objective of this thesis was to extend the study of performance monitoring to more ecological conditions, in which monitoring occurs during continuous motor tasks under various degrees of error and confidence level. We first investigated the role of actions in performance monitoring together with metacognitive judgments, using simultaneous EEG and fMRI recordings. To dissociate the role of motor actions, we designed an experimental paradigm in which subjects had to rate their confidence level about an action that they had either performed themselves (a button press) based on a decision or passively observed (a virtual hand displayed). We found correlates of confidence in both condition, in the EEG and in the supplementary motor area (SMA). Furthermore, we found that subject showed better metacognitive performances when they were the agents of the action. This difference was further emphasized for subjects that showed higher activations of a network previously linked to motor inhibition and comprising the pre-SMA and inferior frontal gyrus (IFG). Our results imply that the SMA plays a primary role in the monitoring of performance, irrespectively of a commitment to a decision and the resulting action. Our findings also suggest that the additional neural processes leading to decisions and actions can inform the metacognitive judgments. In the following chapters, we ask whether electrophysiological correlates of performance monitoring can be found in less experimentally constrained paradigms for which motor output continuous unfolds and visual feedback is not segregated into discrete events. By decomposing the unfolding hand kinematics during a visuo-motor tracking task into periodic acceleration pulses âhenceforth referred to as sub-movements, we found three electrophysiological markers that could possibly be linked to performance monitoring. Firstly, we found an ERP in the SMA, time-locked to sub-movements which encoded the deviation of the hand, 110 ms before. Secondly, we found high-gamma activity in the ACC and SMA of epileptic patients, that was phase-locked to sub-movements. Thirdly, we found a transient modulation of mu oscillations over the ipsilateral sensorimotor cortices that depended on sub-movement amplitude. Altogether, these results provide a strong contribution in the understanding of the neurophysiological processes underlying performance monitoring. Our work proposes a methodological framework to study electrophysiological correlates of performance monitoring in less controlled paradigms during which continuous visual feedback has to be constantly integrated into motor corrections. In the conclusion chapter, we propose a way of extending current models of performance monitoring and decision making to explain the findings of this thesis by considering continuous motor tasks as a succession of decision making processes under time pressure and uncertainty