Mental Blocks: The behavioural effects and neural encoding of obstacles when reaching and grasping

The ability to adeptly interact with a cluttered and dynamic world requires that the brain simultaneously encode multiple objects. Theoretical frameworks of selective visuomotor attention provide evidence for parallel encoding (Baldauf & Deubel, 2010; Cisek & Kalaska, 2010; Duncan, 2006) where concurrent object processing results in neural competition. Since the end goal of object representation is usually action, these frameworks argue that the competitive activity is best characterized as the development of visuomotor biases. While some behavioural and neural evidence has been accumulated in favour of this explanation, one of the most striking, yet deceptively common, demonstrations of this capacity is often overlooked; the movement of the arm away from an obstacle while reaching for a target object is definitive proof that both objects are encoded and affect behaviour. In the current thesis, I discuss three experiments exploring obstacle avoidance. While some previous studies have shown how visuomotor biases develop prior to movement onset, the dynamics of the bias during movement remains largely unexplored. In the first experiment I use the availability and predictability of vision during movement as a means of exploring whether obstacle representations might change during a reach (Chapter 2, Chapman & Goodale, 2010b). While the visuomotor system seems optimized to use vision, I found no difference between reaching with and without vision, providing no evidence that obstacle representations were altered. To more directly test this question, in the second experiment participants made reaches to a target that sometimes changed position during the reach (Chapter 3, Chapman & Goodale, 2010a). The automatic online corrections to the new target location were sometimes interfered with by an obstacle. Using this more direct approach we found definitive evidence that obstacle representations were accessed or updated during movement. In the third experiment, I directly tested the neural encoding of obstacles using functional magnetic resonance imaging (Chapter 4, Chapman, Gallivan, Culham, & Goodale, 2010). When participants planned a grasp movement that was interfered with by an obstacle versus when the grasp was not interfered with, one area in the left posterior intraparietal sulcus was activated. This activity was concurrent with a suppression of early visual areas that were responsive to the position of the obstacle. This study confirmed that the PPC was involved with the encoding of obstacles, and demonstrated that one effect of interference was the suppression of the visual cortical signal associated with the obstacle. These findings extend our understanding of competitive visuomotor biases. Critically, in a world filled with potential action targets, the selection of one target necessarily means all other objects in the workspace are potential obstacles. My results indicate that the visuomotor biasing signal to inhibit obstacle activity is putatively provided by the PPC, which in turn causes the visual cortical representation of the obstacle to be suppressed. The behavioural result of biasing the visual input is the propagation of this suppression to the motor output - ultimately resulting in a reach which intelligently deviates away from potential obstacles

Dynamics of eye-hand coordination are flexibly preserved in eye-cursor coordination during an online, digital, object interaction task

Do patterns of eye-hand coordination observed during real-world object interactions apply to digital, screen-based object interactions? We adapted a real-world object interaction task (physically transferring cups in sequence about a tabletop) into a two-dimensional screen-based task (dragging-and-dropping circles in sequence with a cursor). We collected gaze (with webcam eye-tracking) and cursor position data from 51 fully-remote, crowd-sourced participants who performed the task on their own computer. We applied real-world time-series data segmentation strategies to resolve the self-paced movement sequence into phases of object interaction and rigorously cleaned the webcam eye-tracking data. In this preliminary investigation, we found that: 1) real-world eye-hand coordination patterns persist and adapt in this digital context, and 2) remote, online, cursor-tracking and webcam eye-tracking are useful tools for capturing visuomotor behaviours during this ecologically-valid human-computer interaction task. We discuss how these findings might inform design principles and further investigations into natural behaviours that persist in digital environments

High resolution charge-exchange spectroscopic measurements of aluminum impurity ions in a high temperature plasma

Charge-exchange recombination spectroscopy, which is generally used to measure low-Z impurities in fusion devices, has been used for measuring Al+11 and Al+13 impurities in the Madison Symmetric Torus reversed field pinch. To obtain the impurity ion temperature, the experimental emission spectrum is fitted with a model which includes fine structure in the atomic transition. Densities of these two ionization states, calculated from charge-exchange emission brightness, are used in combination with a collisional radiative model to estimate the abundance of all other charge states of aluminum in the plasma and the contribution of aluminum to the effective ionic charge of the plasma

A Cognitive Ethology Study of First- and Third-Person Perspectives

The present investigation was funded by a grant awarded to AK by the Natural Sciences and Engineering Council of Canada. The funders had no role in study design, data collection, and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD

The Modeled Lifetime Cost-Effectiveness of Published Adherence-Improving Interventions for Antihypertensive and Lipid-Lowering Medications

AbstractObjectiveWe sought to compare the cost-effectiveness of different interventions that have been shown to improve adherence with antihypertensive and lipid-lowering therapy, by combining a burden of nonadherence model framework with literature-based data on adherence-improving interventions.MethodsMEDLINE was reviewed for studies that evaluated ≥1 adherence intervention compared with a control, used an adherence measure other than self-report, and followed patients for ≥6 months. Effectiveness was assessed as Relative Improvement, ratio of adherence with an intervention versus control. Costs, standardized to 12 months and adjusted to 2007 US$, and effectiveness estimates for each intervention were entered into a previously published model designed to measure the burden of nonadherence with antihypertensive and lipid-lowering medications, in a hypertensive population. Outputs included direct medical costs and incremental costs per quality-adjusted life-year (QALY) gained.ResultsAfter screening, 23 eligible adherence-improving interventions were identified from 18 studies. Relative Improvement ranged from 1.13 to 3.60. After eliminating more costly/less effective interventions, two remained. Self-monitoring, reminders, and educational materials incurred total health-care costs of$17,520, and compared with no adherence intervention, had an incremental cost-effectiveness ratio (ICER) of $4984 per QALY gained. Pharmacist/nurse management incurred total health-care costs of$17,896, and versus self-monitoring, reminders, and education had an ICER of $6358 per QALY gained.ConclusionsOf published interventions shown to improve adherence, reminders and educational materials, and a pharmacist/nurse management program, appear to be cost-effective and should be considered before other interventions. Understanding relative cost-effectiveness of adherence interventions may guide design and implementation of efficient adherence-improving program

Adaptive patch foraging in deep reinforcement learning agents

Patch foraging is one of the most heavily studied behavioral optimization challenges in biology. However, despite its importance to biological intelligence, this behavioral optimization problem is understudied in artificial intelligence research. Patch foraging is especially amenable to study given that it has a known optimal solution, which may be difficult to discover given current techniques in deep reinforcement learning. Here, we investigate deep reinforcement learning agents in an ecological patch foraging task. For the first time, we show that machine learning agents can learn to patch forage adaptively in patterns similar to biological foragers, and approach optimal patch foraging behavior when accounting for temporal discounting. Finally, we show emergent internal dynamics in these agents that resemble single-cell recordings from foraging non-human primates, which complements experimental and theoretical work on the neural mechanisms of biological foraging. This work suggests that agents interacting in complex environments with ecologically valid pressures arrive at common solutions, suggesting the emergence of foundational computations behind adaptive, intelligent behavior in both biological and artificial agents.Comment: Published in Transactions on Machine Learning Research (TMLR). See: https://openreview.net/pdf?id=a0T3nOP9s

Counting on the motor system: Rapid action planning reveals the format- and magnitude-dependent extraction of numerical quantity

Symbolic numbers (e.g., 2 ) acquire their meaning by becoming linked to the core nonsymbolic quantities they represent (e.g., two items). However, the extent to which symbolic and nonsymbolic information converges onto the same internal core representations of quantity remains a point of considerable debate. As nearly all previous work on this topic has employed perceptual tasks requiring the conscious reporting of numerical magnitudes, here we question the extent to which numerical processing via the visual-motor system might shed further light on the fundamental basis of how different number formats are encoded.We show, using a rapid reaching task and a detailed analysis of initial arm trajectories, that there are key differences in how the quantity information extracted from symbolic Arabic numerals and nonsymbolic collections of discrete items are used to guide action planning. In particular, we found that the magnitude derived from discrete dots resulted in movements being biased by an amount directly proportional to the actual quantities presented whereasthe magnitude derived from numerals resulted in movements being biased only by the relative (e.g., larger than) quantities presented. In addition, we found that initial motor plans were more sensitive to changes in numerical quantity within small (1-3) than large (5-15) number ranges, irrespective of their format (dots or numerals). In light of previous work, our visual-motor results clearly show that the processing of numerical quantity information is both format and magnitude dependent. © 2014 ARVO

Quasi-single helicity spectra in the Madison Symmetric Torus

Evidence of a self-organized collapse towards a narrow spectrum of magnetic instabilities in the Madison Symmetric Torus [R. N. Dexter, D. W. Kerst, T. W. Lovell, S. C. Prager, and J. C. Sprott, Fusion Technol. 19, 131 (1991)] reversed field pinch device is presented. In this collapsed state, dubbed quasi-single helicity (QSH), the spectrum of magnetic modes condenses spontaneously to one dominant mode more completely than ever before observed. The amplitudes of all but the largest of the m=1 modes decrease in QSH states. New results about thermal features of QSH spectra and the identification of global control parameters for their onset are also discussed