Melbourne School of Psychological Sciences - Theses
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ItemThe temporal dynamics of neural processing of static and moving objects( 2023-01)Transmission and processing of information takes time. In the case of motion perception, the brain could theoretically compensate for these delays by using information about a moving object's past trajectory to predict where the object is located at the present moment. This thesis aimed to explore the neural delays that accumulate during visual processing in humans, and whether these can be compensated during perception of objects moving with a predictable trajectory. In Study 1, we used forward encoding modelling of EEG data to show that, after onset of a simple, static stimulus, the spatial specificity of the neural representation of the stimulus fluctuated over time. This indicates that stimulus processing unfolds in a series of feedforward and feedback sweeps of neural activity through regions of the visual cortex consisting of neurons with varying receptive field sizes. Following this, in Study 2, we again used multivariate analysis of EEG data to investigate the neural response to moving stimuli, to discover whether the brain extrapolates the position of moving objects to compensate for neural delays. We found that objects moving into a position on the screen were represented in that location much earlier than if they were flashed in the same position. This predictive encoding of position served to fully compensate for the delays that accumulate during early stimulus processing. Finally, in Study 3, we investigated the consequences of compensation for delays on perception. In the High-Phi illusion, uncorrelated noise textures are interpreted as motion due to a rotating inducing texture; we show that perception of illusory motion can be explained by extrapolation of the preceding motion. Furthermore, the perceived position of a flashed static object was biased by these predictive signals, and the magnitude of illusory motion jumps and position shifts scaled with the speed of the inducing motion. Overall, these results show that processing even simple visual information takes time, but this time can be compensated when viewing predictable visual motion, leading to changes in neural coding and perception of moving objects.
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ItemThe Cognitive and Neural Mechanisms of Dietary Decision-Making( 2022)Dietary decisions are influential on both physical and mental health. Unhealthy choices can have many negative consequences, including obesity, heart disease, diabetes, and cancer. This thesis investigated the role of tastiness and healthiness in dietary decisions and interventions, with three specific research questions. The first involved neural representations of tastiness and healthiness: more specifically, how these attributes are represented in the brain during the early stages of dietary decisions. The second question was centred on whether health warning labels (HWLs) can reduce sugary drink consumption. Finally, the third question involved how the experience and regulation of incidental emotions impacts dietary decisions. These questions were addressed in the three empirical chapters of this thesis. In Study 1, we investigated neural representations of tastiness and healthiness during the first second of rating food images (Experiment 1) or consumption decisions (Experiment 2). The results showed that fine-grained taste and health ratings could be decoded from electroencephalography data using multivariate pattern analysis. This suggests that during dietary decisions, tastiness and healthiness representations are present in the brain from an early stage, even without explicit instructions to consider them. In Study 2, we investigated whether HWLs encouraged healthier choices regarding sugar-sweetened beverages. In a laboratory-based task, participants viewed HWLs, then indicated their willingness to consume various beverages. The HWLs referred either to consequences of a poor diet (general) or sugary drinks (specific). The results showed that both types of HWLs decreased willingness to consume drinks, compared to a control condition. For general HWLs, this effect was weaker for drinks perceived as healthy, whereas the effect of specific HWLs remained constant regardless of perceived healthiness. Overall, our results suggest that HWLs may be effective at prompting behaviour change, and product-specific messages may reduce consumption of a wider range of drinks. In Study 3, we examined how dietary decisions are influenced by emotions and the regulation of these emotions. Participants completed an online task which involved experiencing and regulating emotions before making hypothetical dietary decisions. The results showed that negative emotions decreased willingness to consume foods, whereas positive emotions led to an increase, particularly for healthy foods. Regulating negative emotions did not change dietary decisions; however, actively increasing and decreasing positive emotions via reappraisal led to respective increases and decreases in desire for food. These results may suggest that people appraise stimuli in a way that matches their emotional state (e.g., feeling positive leads people to view foods as more pleasant). Overall, these findings highlight the importance of both healthiness and tastiness for dietary decision-making, support the effectiveness of HWLs for promoting healthier choices, and deepen our understanding of the effects of incidental emotions and emotion regulation on dietary decisions. This thesis may inform interventions to improve dietary decisions, and provides a strong basis for future studies that aim to evaluate interventions through examining changes to neural representations of taste and health attributes.
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ItemPrediction and neural transmission delays in visual motion processing( 2022)Neural transmission takes time. Although this delay is seemingly insignificant (approximately 70 ms), it complicates the real-time localization of moving objects because the brain has no access to information about where the object is now. In this thesis, we study how prediction, and motion extrapolation in particular, can help overcome these neural transmission delays in visual motion processing. For motion extrapolation mechanisms to do this, they need to be able to drive sensory representations in the absence of sensory information, since sensory information arrives on a delayed time-line. In Study 1, we find that sensory representations corresponding to the anticipated next location on a motion trajectory are pre-activated before the anticipated stimulus onset and the arrival of sensory information. Correspondingly, in Study 2, we find that moving objects are subsequently represented with a shorter latency. To explain these findings, we outline a neural architecture of horizontal and feedback connections inducing pre-activations at anticipated stimulus locations that fits within the current dominant framework of cortical organization. The consequence of such an architecture however is that, when a moving object diverges from its predictable trajectory, the wrong stimulus location has been pre-activated. We show that, faced with a motion prediction violation, the brain indeed briefly represents the object in the anticipated but never presented stimulus location, resulting in a latency disadvantage for the representation of the mispredicted stimulus. In Study 3 we finally demonstrate that the overextrapolation is actively corrected for, preventing the conscious percept of the stimulus in the overextrapolated location.
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ItemBelief updating and information seeking in decision making under uncertainty( 2017)Adaptive goal-directed behaviour depends on a well-calibrated internal model of the environment. In particular, learning and decision making is most efficient when there is a good match between an agent’s model of the environment and true environmental contingencies. Accordingly, recent theories in cognitive neuroscience have proposed that a primary computational goal of the central nervous system in humans and other animals is the construction and maintenance of these internal models (also termed beliefs). The present thesis aimed to investigate the implications of this belief-centric perspective for the study of decision making under uncertainty, using computational modelling of behaviour in concert with analysis of human electroencephalography (EEG) data. Across one behavioural and three EEG studies, this thesis addressed two related questions concerning participants’ updating of beliefs. Study 1 and Study 2 sought to characterise the neural and cognitive processes by which participants incorporated new information into their beliefs (belief updating). Study 3 and Study 4 sought to investigate the nature of participants’ preferences for acquiring such information, and the neural substrates of this preference (information seeking). In Study 1, 18 healthy young adult participants completed a perceptual learning task—in which participants learned to identify the target contrast of a greyscale checkerboard stimulus using monetary feedback—while EEG was recorded. Formal comparison of computational cognitive models revealed that participants’ behaviour in this task was better explained by a model implementing Bayesian belief updating than by a model implementing a simpler win-stay lose-shift (WSLS) heuristic. Belief variables computed from this Bayesian model were then used as predictors in a single-trial regression analysis of event-related potential (ERP) data. This analysis revealed that the amplitude of the frontocentral P3 component of the ERP was positively associated with belief update size, and that the amplitude of the stimulus-preceding negativity component was negatively associated with belief uncertainty. These results provided evidence that belief update size and belief uncertainty had distinct neural signatures that could be tracked in single trials in specific ERP components. The results further suggested that the cognitive mechanisms underlying belief updating in this task could be described well within a Bayesian framework. Study 2 investigated the effect of task motivation on participants’ use of Bayesian versus heuristic task strategies, and upon the neural substrates of belief updating. Using a modified variant of the perceptual learning task from Study 1, Study 2 presented feedback to participants in the form of either monetary reward, or as affectively neutral instructional directives. Using model-based clustering based upon formal comparison of computational cognitive models, Study 2 identified two distinct participant subgroups. The first subgroup used Bayesian inference in the monetary condition, but switched to a heuristic strategy in the instructive feedback condition; by contrast, the second subgroup always used the Bayesian inference strategy, regardless of feedback condition. It was found that only the strategy-switching subgroup showed worse performance for instructive than for monetary feedback, whereas the Bayesian subgroup did not. This pattern of performance was reflected by similar differences between subgroups in neural encoding of feedback in two components of the event-related potential: the P3, and the late positive potential. These findings suggested that selection of Bayesian versus heuristic strategies in perceptual learning may depend critically on participants’ motivational state, and that individual differences in strategy-switching may underlie group-level differences in neural encoding of feedback. Study 3 investigated information seeking behaviour in two experiments, each with 40 healthy participants. In these experiments, participants completed a novel information-seeking task in which they could choose to pay a monetary cost to receive advance information about the outcome of a monetary lottery. Importantly, acquiring information did not alter lottery outcome probabilities. In the first experiment, it was found that participants were willing to incur considerable monetary costs to acquire payoff-irrelevant information about the lottery outcome. This behaviour was well explained by a computational cognitive model in which information preference resulted from aversion to temporally prolonged uncertainty. In the second experiment, it was found that preference for information was modulated by the rate of information delivery. These results strongly suggest that humans assign an intrinsic value to information, in a manner inconsistent with normative accounts of decision making under uncertainty. Finally, Study 4 investigated the neural substrates of the intrinsic valuation of information, using EEG data were recorded from 22 participants performing the information seeking task developed in Study 3. Behavioural results replicated the findings of Study 3. Analysis of ERPs elicited by informative cues revealed that the feedback-related negativity, an ERP component linked to reward processing, independently encoded both a reward prediction error and an information prediction error. These findings are consistent with the hypothesis that information seeking results from processing of information within neural reward circuits, and provide further evidence for an intrinsic valuation of information. Overall, these findings demonstrate that a belief-centric research perspective has substantial explanatory power for behavioural and neural data in human decision making under uncertainty.
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ItemCerebello-cortical and fronto-parietal contributions to working memory function in children born extremely preterm: a diffusion MRI study( 2016)Survivors of extremely preterm birth (<28 weeks’ gestation) and/or extremely low birth weight (<1000 grams) have elevated rates of working memory impairment compared with term-born peers. This impairment may be a core deficit underlying problems experienced by these children in other areas of cognitive, behavioural and academic functioning. Extremely preterm survivors are also at risk of white matter injury and cerebellar injury as a result of neurological disruptions associated with preterm birth. However, it is not yet known whether this injury and developmental disruption to cerebellar white matter connections underlies the working memory deficits seen in this population. It is also unclear whether working memory deficits may be ameliorated through intensive working memory training, and whether white matter microstructural plasticity underlies training gains in working memory capacity. This thesis aimed to examine whether variability in the maturity and microstructural organisation of white matter pathways associated with working memory were related to working memory ability in a group of 7-year-old extremely preterm children. It also aimed to evaluate whether working memory capacity and white matter microstructure were capable of change (functional and neuroplastic change, respectively), in response to the most widely evaluated adaptive working memory training intervention, Cogmed. Sixty participants were recruited from a large cohort of 7-year-old extremely preterm children born in Victoria, Australia. Two white matter pathways in the brain were investigated using probabilistic tractography with diffusion-weighted MRI; the superior longitudinal fasciculus (SLF), a monosynaptic fronto-parietal white matter tract well-recognised for its involvement in working memory function, and the cerebello-thalamo-prefrontal (CTP) pathway, a polysynaptic efferent cerebellar white matter pathway hypothesised to be involved in working memory function. The CTP pathway was further divided into two monosynaptic components; the cerebello-thalamic tract (CT), and the thalamo-prefrontal tract (TP). The diffusion-weighted MRI measures of fractional anisotropy, axial diffusivity, radial diffusivity, and mean diffusivity were used to assess white matter microstructure. The Cogmed working memory training intervention (5-7 weeks) was administered using a double-blinded, placebo-controlled, randomised control trial. In the adaptive Cogmed intervention, activities became more complex with increasing proficiency of the participant, thereby challenging working memory capacity. In the placebo Cogmed intervention, activities remained at a fixed, low level of difficulty. Working memory capacity and white matter microstructure were assessed at baseline and two-weeks post-intervention using gold-standard measures. The study found that, prior to the intervention, immaturity of microstructural connectivity in cerebello-thalamo-prefrontal and fronto-parietal white matter pathways was related to lower working memory performance. Following the intervention, no significant difference in working memory performance or microstructural white matter maturity was noted in children who undertook adaptive versus placebo training. The novel finding of this thesis is that early disruption to the microstructural development of cerebello-cortical white matter pathways (as a result of extremely preterm birth) may represent a potential neurobiological mechanism underlying working memory dysfunction in this population. Evaluation of these tracts in the perinatal period therefore has the potential to identify children at risk of developing working memory deficits later in life, so that close surveillance or early interventions may be applied. However, Cogmed adaptive (versus placebo) working memory training does not appear to be an effective intervention in improving working memory capacity for school-age extremely preterm children.