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<p>During task-switching, if we occasionally encounter stimuli that cue more than one task (i.e. bivalent stimuli), response slowing is observed on all univalent trials within that block, even when no features overlap with the bivalent stimuli. This observation is known as the bivalency effect. Here, I show that the bivalency effect reflects a form of top-down cognitive control that is not easily explained by most current models of control in the literature. The research presented within my thesis reveals that the bivalency effect reflects an adjustment in cognitive control that is highly dependent on past experience with response conflict (chapters 4 and 5), violations of expectancy (chapter 3 and 5), and recent inhibition (chapters 3, 4, and 5). Furthermore, the processes in response to these factors are likely captured by the dorsal anterior cingulate cortex (dACC) and the temporal parietal junction (TPJ) (chapters 2 and 5), reflecting responses to inhibitory demands, and extra visual feature extraction after encountering bivalent stimuli, respectively. These findings provide support for a recent cognitive control model that suggests that the role of the ACC is to track current and recent changes in the environment in order to optimize future performance by predicting changes in cognitive demand (Sheth et al., 2012).</p> / Doctor of Philosophy (PhD)

<p>Recent research on cognitive control has focused on the learning consequences of high selective attention demands in selective attention tasks. The current study extends these ideas by examining the influence of selective attention demands on remembering. In Experiment 1, participants read aloud the red word in a pair of red and green interleaved words. Half of the items were congruent (the interleaved words were the same), and the other half were incongruent (the interleaved words were different). Following the study phase, participants completed a recognition memory test with a remember/know classification. A mirror effect was observed in the recognition memory data, with better memory for incongruent than for congruent items. In Experiment 2, context was only partially reinstated at test, and again better memory for incongruent compared to congruent items was observed. However, the processes supporting recognition decisions varied depending on context reinstatement, with only full context reinstatement resulting in differences in recollection for congruent and incongruent items. These results demonstrate that selective attention process demands associated with incongruent items affect episodic learning.</p> / Master of Science (MSc)

Eating disorders involve the inability to appropriately regulate a behavioral response to food due to impaired reward sensitivity, affect regulation and cognitive control, resulting in deleterious effects on the individual's physical and mental well-being. In this way eating disorders may be analogous to addictive disorders (e.g. alcoholism). Furthermore, eating and addictive disorders co-occur at very high rates and appear to have similar contributing mechanisms (impaired reward sensitivity, impaired affect regulation and impaired cognitive control). Overvaluation of weight and shape concerns appears to be one unique characteristic of eating disorders, not shared with addiction. The current study examined the relationship between impaired reward sensitivity, impaired affect regulation and impaired cognitive control with addiction vulnerability. Furthermore, weight and shape concerns were examined as a potential moderator of the relationship between addiction vulnerability and binge eating. A total of 1000 undergraduate students completed self-report measures examining the three posited mechanisms for addiction vulnerability and disordered eating. A subset of 101 students (50 binge-eaters and 51 non-binge eaters) also completed behavioral measures of the three posited mechanisms. The results of this study support the proposed model that weight and shape concerns moderate the relationship between addiction vulnerability and binge eating. Results also demonstrated on a behavioral task that individuals who endorsed binge eating were more likely to act impulsively and quit the PASAT-C task faster than control subjects. Furthermore, they demonstrated a greater increase in irritability while completing the task which may have resulted in their desire to quit the task earlier. No differences were found on behavioral measures of reward sensitivity (delay discount task) or cognitive control (stop signal task). Future studies should continue to examine the construct of addiction vulnerability to provide additional validity for the construct as well as examine it in the context of all forms of disordered eating. / Psychology

People’s decisions regarding effort-based tasks such as engaging in physical activity depend on the subjective value of the activity: weighing the costs against the benefits (Chong et al., 2016). Exerting cognitive effort while performing one task negatively biases people's decisions to exert effort on subsequent cognitive tasks, suggesting a shift in their subjective valuation of the task due to mental fatigue (Kool & Botvinick, 2014). Similarly, exerting physical effort negatively biases decisions to further exert effort on a future physical task (Iodice et al., 2017a, Iodice et al., 2017b). The purpose of the present study was to investigate the effect of mental fatigue on people's decisions to engage in an acute bout of exercise and whether the effect of mental fatigue on decision-making was mediated by a benefit-cost analysis. Among those who decided to exercise, the study also aimed to investigate the relationship between mental fatigue and exercise behaviours during a self-selected, self-paced, bout of exercise. Recreationally active participants (N = 55, Mage = 19.04 ± 1.04 years) completed either a 10-minute, high cognitive demand (Stroop) task or low cognitive demand (documentary viewing) task to manipulate levels of mental fatigue. Participants then made a choice between engaging in a 20-minute self-paced moderate-to-vigorous intensity exercise task or a 20-minute non-exercise task. Prior to choosing, participants rated their mental fatigue and their perceived benefits and costs of the exercise task. The cognitive task had a strong effect on mental fatigue (p < .001, Cohen's d = 1.40). The mediation analysis showed no direct effect of mental fatigue on choice; however, there was a significant indirect effect indicating the benefit-cost score mediated the effect of mental fatigue on choice (95% C.I. = -.02 to -.0004). Higher levels of mental fatigue were associated with a lower benefit-cost score (r = -.33, p = .01) which, in turn, was associated with a decreased likelihood of choosing the exercise task (r = .31, p = .02). For those who chose to engage in the exercise task (N = 28), higher levels of mental fatigue were associated with higher ratings of perceived exertion (r = .38, p = .05). Findings provide insight into the effects of mental fatigue on people's exercise behaviours, illustrating a rational decision-making process that is dependent upon the subjective evaluation of the costs and benefits of engaging in physical activity or sedentary alternatives. / Thesis / Master of Science (MSc)

In this dissertation, I have addressed the question of how resting-state EEG markers primarily in the alpha frequency range are linked to general cognitive performance and age. In the three studies presented in the work, I show that alpha power, frequency, and temporal dynamics, have distinct contributions to cognitive control functions in different age groups. Moreover, individual alpha peak frequency as well as the slope of 1/f decay of the PSD shows consistent age-related alterations, while alpha power is linked to structural alterations in the white matter. Our research extends further existing literature by specifying relevant neural networks as well as important methodological considerations that should be taken into account when analysing properties of oscillations.

<p dir="ltr">This work provides a new framework for investigating instances where multitasking and focusing do not need to trade off, but can rather coexist.</p>

Although numerous studies have closely examined the processes by which working memory (WM) updates and maintains information, there has been a paucity of research examining the switching mechanism between these two WM functions. O’Reilly & Frank (2006) proposed that the switching process is governed by a WM 'gate' that opens the gate to switch WM function from maintenance to updating and closes the gate to reverse the process. It is noteworthy that subsequent studies have consistently observed an asymmetry between opening and closing the WM gate. This asymmetry is manifested as a higher time cost but a lower error rate when closing the WM gate than when opening the gate. Until now, this asymmetry and the WM gating process have not been well understood. The objective of my dissertation was to elucidate the essential components of WM gating processes that determine the asymmetry between opening and closing. In particular, the roles of inhibitory control (on the state of the WM gate switches from) and intentional control (on the state the gate switches to) were investigated. A total of four studies were conducted in stages. The first study extracted the neurophysiological constituents of WM gating processes. The second study investigated the difference in effort investment between WM gate opening and closing. Another two studies further explored the causality of the asymmetry via brain stimulation methods. All studies replicated the behavioral asymmetry between gate opening and closing (lower error rate and higher time cost for gate closing). A common neurophysiological pathway of the WM gating cascade from the ventral stream to the frontal cortex was revealed, suggesting that WM gate opening and closing follow common steps of inhibition of the previous gate state and reactivation of the required gate state. Nevertheless, the ventral stream distinguished residual preceding gate activation, whereby a stronger preceding gate state (open) remained highly activated before closing than gate-close state before opening and subsequently affected inhibitory control over it. Additionally, distinct frontal activities were observed between opening and closing, indicating a switch of attention to different sources. Strong intentional control was involved to direct the attention to sensory information during gate opening. These findings suggest that the opening of the WM gate is more effortful than the closing of the WM gate, which is perceived as more natural and effortless. It is likely that the human brain tends to maintain the WM in a closed state, and this default tendency to close the WM gate may be the origin of the asymmetry in gating performance. This knowledge sheds the light on the mechanism of WM controls and suggests a potential for predicting the developmental patterns of WM and WM deficiencies in psychiatric disorders.:PREFACE III ACKNOLEDGEMENTS V LIST OF FIGURES XI LIST OF TABLES XIII INDEX OF ABBREVATIONS XV ABSTRACT XVII CHAPTER 1 INTRODUCTION 1 1.1 A general introduction 3 1.2 What is the gating of WM? 4 1.3 Cognitive processes associated with WM gating 6 1.3.1 Switching-inspired view of WM gating mechanism 6 1.3.2 Inhibitory control and its potential association with gating cost in time 7 1.3.3 Intentional control and its potential association with gating accuracy 9 1.3.4 My hypothesized model of WM gating 9 1.4 Neurophysiological and anatomical associations with the WM gating process 11 1.4.1 The role of alpha band activities in the inhibition of the preceding gate 12 1.4.2 The role of theta band activities in the reconfiguration of the new WM gate 13 1.4.3 The prefrontal cortex potentially executes the WM gating 14 1.4.4 Associations between the WM gating and the frontoposterior network 15 1.5 Neurobiological underpinnings of the WM Gating 16 1.5.1 The GABAergic system and its associations with inhibitory control 16 1.5.2 The norepinephrine system and its associations with intentional control 17 CHAPTER 2 HYPOTHESES AND METHODOLOGIES 19 2.1 General hypotheses and objectives 21 2.2 Research questions and study design 22 2.2.1 The paradigm: reference-back task 22 2.2.2 Study 1: whether and how are WM gating processes constituted? 24 2.2.3 Study 2: how do individuals engage in WM gating processes? 25 2.2.4 Study 3: how does effort affect WM gating? 26 2.2.5 Study 4: what drives the difference between WM gate opening and closing? 28 CHAPTER 3 STUDIES 31 3.1 Study 1: a ventral stream-prefrontal cortex processing cascade enables WM gating dynamics 33 3.1.1 Abstract 33 3.1.2 Introduction 33 3.1.3 Results and Discussion 37 3.1.4 Methods 47 3.1.5 Competing interests 55 3.1.6 Data availability 55 3.1.7 Code availability 55 3.1.8 Acknowledgements 55 3.2 Study 2: time-on-task effects on WM gating processes—a role of theta synchronization and the norepinephrine system 55 3.2.1 Abstract 55 3.2.2 Introduction 56 3.2.3 Materials and Methods 60 3.2.4 Results 66 3.2.5 Discussion 71 3.2.6 Acknowledgements 74 3.2.7 Funding 74 3.2.8 Conflicts of Interest 75 3.2.9 Availability of data and materials 75 3.3 Study 3: atVNS specifically enhances WM gate closing mechanism 75 3.3.1 Abstract 75 3.3.2 Significance statement 76 3.3.3 Introduction 76 3.3.4 Materials and Methods 78 3.3.5 Results 92 3.3.6 Discussion 103 3.3.7 Data and code availability statement 107 3.3.8 Conflict of interest statement 107 3.3.9 Acknowledgements 107 3.4 Study 4: inhibitory control in WM gate opening: insights from alpha desynchronization and norepinephrine activity under atDCS stimulation 108 3.4.1 Abstract 108 3.4.2 Introduction 108 3.4.3 Materials and Methods 112 3.4.4 Results 121 3.4.5 Discussion 126 3.4.6 Acknowledgements 131 3.4.7 Conflicts of interest 131 3.4.8 Ethics Statement 131 3.4.9 Data and Code Availability Statement 131 CHAPTER 4 DISCUSSION 133 4.1 Summary of findings 135 4.2 The ventral stream-frontal cortex pathway of the WM gating 137 4.2.1 The ventral stream distinguishes the residual preceding gate activation 137 4.2.2 A possible hub of suppressing the preceding gate state in the parietal lobe 139 4.2.3 A cascade towards frontal cortices for reconfiguring new gate state 141 4.2.4 Distinct neural networks between opening and closing 142 4.2.5 WM gating as a switch toward external and internal information 144 4.3 Neural modulations of the WM gating process 145 4.3.1 Cognitive demands of the WM gating and NE’s modulation 145 4.3.2 The modulatory role of GABA and accompanied ABA in WM gating 148 4.4 Implications for future studies 149 4.4.1 What is the difference between WM gating and task switching? 149 4.4.2 What is the key to opening or closing the WM gate? 150 4.4.3 Is the gate-close the real default mode of the WM gate? 151 4.5 Limitations and Conclusion 153 4.5.1 Limitations 153 4.5.2 Conclusion 155 CHATPTER 5 REFERENCE 157 CHAPTER 6 APPENDEX 191 6.1 Supplementary materials for Study 1 193 6.2 Supplementary figures for Study 2 196 DECLARATION 199