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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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.