Publications by authors named "Matthew J Crossley"

Objective: This review surveys the literature on sensorimotor challenges impacting performance in laparoscopic minimally invasive surgery (MIS).

Background: Despite its well-known benefits for patients, achieving proficiency in MIS can be challenging for surgeons due to many factors including altered visual perspectives and fulcrum effects in instrument handling. Research on these and other sensorimotor challenges has been hindered by imprecise terminology and the lack of a unified theoretical framework to guide research questions in the field.

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Integrating sensory information during movement and adapting motor plans over successive movements are both essential for accurate, flexible motor behaviour. When an ongoing movement is off target, feedback control mechanisms update the descending motor commands to counter the sensed error. Over longer timescales, errors induce adaptation in feedforward planning so that future movements become more accurate and require less online adjustment from feedback control processes.

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There is an unresolved question about whether realigned visual feedback is beneficial or costly to laparoscopic task performance. We provide evidence that camera realignment imposes a reliable cost on performance across both naive controls and experienced surgeons. This finding clarifies an important ongoing discussion in the literature about the effects of camera realignment, which could inform the strategies that laparoscopic surgeons use in the operating room.

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Although human motor learning has been intensively studied for many decades, it remains unknown whether group differences are present in expert cohorts that must routinely cope with and learn new visuomotor mappings such as expert minimally invasive surgeons. We found that expert surgeons compensate for a visuomotor perturbation more rapidly than naive controls. Modelling indicates that these differences in expert behavioural performance reflects greater trial-to-trial retention, as opposed to greater trial-to-trial learning rate.

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Interventions for drug abuse and other maladaptive habitual behaviors may yield temporary success but are often fragile and relapse is common. This implies that current interventions do not erase or substantially modify the representations that support the underlying addictive behavior-that is, they do not cause true unlearning. One example of an intervention that fails to induce true unlearning comes from Crossley, Ashby, and Maddox (2013, Journal of Experimental Psychology: General), who reported that a sudden shift to random feedback did not cause unlearning of category knowledge obtained through procedural systems, and they also reported results suggesting that this failure is because random feedback is noncontingent on behavior.

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Substantial evidence suggests that human category learning is governed by the interaction of multiple qualitatively distinct neural systems. In this view, procedural memory is used to learn stimulus-response associations, and declarative memory is used to apply explicit rules and test hypotheses about category membership. However, much less is known about the interaction between these systems: how is control passed between systems as they interact to influence motor resources? Here, we used fMRI to elucidate the neural correlates of switching between procedural and declarative categorization systems.

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Considerable evidence suggests that human category learning recruits multiple memory systems. A popular assumption is that procedural memory is used to form stimulus-to-response mappings, whereas declarative memory is used to form and test explicit rules about category membership. The multiple systems framework has been successful in motivating and accounting for a broad array of empirical observations over the past 20 years.

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Identifying the strategy that participants use in laboratory experiments is crucial in interpreting the results of behavioral experiments. This article introduces a new modeling procedure called iterative decision-bound modeling (iDBM), which iteratively fits decision-bound models to the trial-by-trial responses generated from single participants in perceptual categorization experiments. The goals of iDBM are to identify: (1) all response strategies used by a participant, (2) changes in response strategy, and (3) the trial number at which each change occurs.

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When a person fails to obtain an expected reward from an object in the environment, they face a credit assignment problem: Did the absence of reward reflect an extrinsic property of the environment or an intrinsic error in motor execution? To explore this problem, we modified a popular decision-making task used in studies of reinforcement learning, the two-armed bandit task. We compared a version in which choices were indicated by key presses, the standard response in such tasks, to a version in which the choices were indicated by reaching movements, which affords execution failures. In the key press condition, participants exhibited a strong risk aversion bias; strikingly, this bias reversed in the reaching condition.

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Unlabelled: Sensorimotor adaptation has traditionally been viewed as a purely error-based process. There is, however, growing appreciation for the idea that performance changes in these tasks can arise from the interplay of error-based adaptation with other learning processes. The challenge is to specify constraints on these different processes, elucidating their respective contributions to performance, as well as the manner in which they interact.

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The basal ganglia are a collection of subcortical nuclei thought to underlie a wide variety of vertebrate behavior. Although a great deal is known about the functional and physiological properties of the basal ganglia, relatively few models have been formally developed that have been tested against both behavioral and physiological data. Our previous work (Ashby FG, Crossley MJ.

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When humans simultaneously execute multiple tasks, performance on individual tasks suffers. Complementing existing theories, this article poses a novel question to investigate interactions between memory systems supporting multi-tasking performance: When a primary and dual task both recruit declarative learning and memory systems, does simultaneous performance of both tasks impair primary task performance because learning in the declarative system is reduced, or because control of the primary task is passed to slower procedural systems? To address this question, participants were trained on either a perceptual categorization task believed to rely on procedural learning or one of three different categorization tasks believed to rely on declarative learning. Task performance was examined with and without a simultaneous dual task thought to recruit working memory and executive attention.

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Virtually all current theories of category learning assume that humans learn new categories by gradually forming associations directly between stimuli and responses. In information-integration category-learning tasks, this purported process is thought to depend on procedural learning implemented via dopamine-dependent cortical-striatal synaptic plasticity. This article proposes a new, neurobiologically detailed model of procedural category learning that, unlike previous models, does not assume associations are made directly from stimulus to response.

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There is now abundant evidence that human learning and memory are governed by multiple systems. As a result, research is now turning to the next question of how these putative systems interact. For instance, how is overall control of behavior coordinated, and does learning occur independently within systems regardless of what system is in control? Behavioral, neuroimaging, and neuroscience data are somewhat mixed with respect to these questions.

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Environmental context can have a profound influence on the efficacy of intervention protocols designed to eliminate undesirable behaviors. This is clearly seen in drug rehabilitation clinics where patients often relapse soon after leaving the context of the treatment facility. A similar pattern is commonly observed in controlled laboratory studies of context-dependent savings in instrumental conditioning, where simply placing an animal back into the original conditioning chamber can renew an extinguished instrumental response.

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Huge amounts of money are spent every year on unlearning programs--in drug-treatment facilities, prisons, psychotherapy clinics, and schools. Yet almost all of these programs fail, since recidivism rates are high in each of these fields. Progress on this problem requires a better understanding of the mechanisms that make unlearning so difficult.

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Categorization is essential for survival, and it is a widely studied cognitive adaptation in humans and animals. An influential neuroscience perspective differentiates in humans an explicit, rule-based categorization system from an implicit system that slowly associates response outputs to different regions of perceptual space. This perspective is being extended to study categorization in other vertebrate species, using category tasks that have a one-dimensional, rule-based solution or a two-dimensional, information-integration solution.

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Unstructured categories are those in which the stimuli are assigned to each contrasting category randomly, and thus there is no rule- or similarity-based strategy for determining category membership. Intuition suggests that unstructured categories are likely to be learned via explicit memorization that is under the control of declarative memory. In contrast to this prediction, neuroimaging studies of unstructured-category learning have reported task-related activation in the striatum, but typically not in the hippocampus--results that seem more consistent with procedural learning than with a declarative-memory strategy.

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A large number of criteria have been proposed for determining when a behavior has become automatic. Almost all of these were developed before the widespread acceptance of multiple memory systems. Consequently, popular frameworks for studying automaticity often neglect qualitative differences in how different memory systems guide initial learning.

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Current theories of human categorization differentiate an explicit, rule-based system of category learning from an implicit system that slowly associates regions of perceptual space with response outputs. The researchers extended this theoretical differentiation to the category learning of New World primates. Four capuchins (Cebus apella) learned categories of circular sine-wave gratings that varied in bar spatial frequency and orientation.

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An essential component of skill acquisition is learning the environmental conditions in which that skill is relevant. This article proposes and tests a neurobiologically detailed theory of how such learning is mediated. The theory assumes that a key component of this learning is provided by the cholinergic interneurons in the striatum known as tonically active neurons (TANs).

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Two experiments tested whether declarative and procedural memory systems operate independently or inhibit each other during perceptual categorization. Both experiments used a hybrid category-learning task in which perfect accuracy could be achieved if a declarative strategy is used on some trials and a procedural strategy is used on others. In the two experiments, only 2 of 53 participants learned a strategy of this type.

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An influential theoretical perspective differentiates in humans an explicit, rule-based system of category learning from an implicit system that slowly associates different regions of perceptual space with different response outputs. This perspective was extended for the 1st time to the category learning of nonhuman primates. Humans (Homo sapiens) and macaques (Macaca mulatta) learned categories composed of sine-wave gratings that varied across trials in bar width and bar orientation.

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