Biology subjects

Taylor, J. A.

Publications and source records attributed to Taylor, J. A..

9 recordsLinked to original sources

bioRxiv2018

Generalization via superposition: Combined effects of mixed reference frame representations for explicit and implicit learning in a visuomotor adaptation task.

Studies on generalization of learned visuomotor perturbations has generally focused on whether learning is coded in extrinsic or intrinsic reference frames. This dichotomy, however, is challenged by recent findings showing that learning is represented in a mixed reference frame. Overlooked in this framework is how learning is the result of multiple processes, such as explicit re-aiming and implicit motor adaptation. Therefore the proposed mixed representation may simply reflect the superposition of explicit and implicit generalization functions, each represented in different reference frames. Here, we characterized the individual generalization functions of explicit and implicit learning in relative isolation to determine if their combination could predict the overall generalization function when both processes are in operation. We modified the form of feedback in a visuomotor rotation task to isolate explicit and implicit learning, and tested generalization across different limb postures to dissociate the extrinsic and intrinsic representations. We found that explicit generalization occurred predominantly in an extrinsic reference frame but the amplitude was reduced with postural changes, whereas implicit generalization was phase-shifted according to a mixed reference frame representation and amplitude was maintained. A linear combination of individual explicit and implicit generalization functions accounted for nearly 85% of the variance associated with the generalization function in a typical visuomotor rotation task, where both processes are in operation. This suggests that each form of learning results from a mixed representation with distinct extrinsic and intrinsic contributions, and the combination of these features shape the generalization pattern observed at novel limb postures.\n\nNew and noteworthyGeneralization following learning in visuomotor adaptation tasks can reflect how the brain represents what it learns. In this study, we isolated explicit and implicit forms of learning, and showed that they are derived from a mixed reference frame representation with distinct extrinsic and intrinsic contributions. Furthermore, we showed that the overall generalization pattern at novel workspaces is due to the superposition of independent generalization effects developed by explicit and implicit learning processes.

neuroscience↗

bioRxiv2018

Can patients with cerebellar disease switch learning mechanisms to reduce their adaptation deficits?

Systematic perturbations in motor adaptation tasks are primarily countered by learning from sensory-prediction errors, with secondary contributions from other learning processes. Despite the availability of these additional processes, particularly the use of explicit re-aiming to counteract observed target errors, patients with cerebellar degeneration are surprisingly unable to compensate for their sensory-prediction-error deficits by spontaneously switching to another learning mechanism. We hypothesized that if the nature of the task was changed - by allowing vision of the hand, which eliminates sensory-prediction errors - patients could be induced to preferentially adopt aiming strategies to solve visuomotor rotations. To test this, we first developed a novel visuomotor rotation paradigm that provides participants with vision of their hand in addition to the cursor, effectively setting the sensory-prediction-error signal to zero. We demonstrated in younger healthy controls that this promotes a switch to strategic re-aiming based on target errors. We then showed that with vision of the hand, patients with spinocerebellar ataxia could also switch to an aiming strategy in response to visuomotor rotations, performing similarly to age-matched participants (older controls). Moreover, patients could retrieve their learned aiming solution after vision of the hand was removed, and retain it for at least one year. Both patients and older controls, however, exhibited impaired overall adaptation performance compared to younger healthy controls (age, 18-33), likely due to age-related reductions in spatial and working memory. Moreover, patients failed to generalize, i.e., they were unable to adopt analogous aiming strategies in response to novel rotations, nor could they further improve their performance without vision of the hand. Hence, there appears to be an inescapable obligatory dependence on sensory-prediction-error-based learning - even when this system is impaired in patients with cerebellar degeneration. The persistence of sensory-prediction-error-based learning effectively suppresses a switch to target-error-based learning, which perhaps explains the unexpectedly poor performance by patients with spinocerebellar ataxia in visuomotor adaptation tasks.

neuroscience↗

bioRxiv2018

Predicting Individual Psychotic Experiences on a Continuum Using Machine Learning

Previous studies applying machine learning methods to psychosis have primarily been concerned with the binary classification of chronic schizophrenia patients and healthy controls. The aim of this study was to use electroencephalographic (EEG) data and pattern recognition to predict subclinical psychotic-like experiences on a continuum between these two extremes in otherwise healthy people. We applied two different approaches to an auditory oddball regularity learning task obtained from N = 73 participants: O_LIA feature extraction and selection routine incorporating behavioural measures, event-related potential components and effective connectivity parameters; C_LIO_LIRegularisation of spatiotemporal maps of event-related potentials. C_LI Using the latter approach, optimal performance was achieved using the response to frequent, predictable sounds. Features within the P50 and P200 time windows had the greatest contribution toward lower Prodromal Questionnaire (PQ) scores and the N100 time window contributed most to higher PQ scores. As a proof-of-concept, these findings demonstrate that EEG data alone are predictive of individual psychotic-like experiences in healthy people. Our findings are in keeping with the mounting evidence for altered sensory responses in schizophrenia, as well as the notion that psychosis may exist on a continuum expanding into the non-clinical population.

neuroscience↗

bioRxiv2018

Plan-based generalization shapes local implicit adaptation to opposing visuomotor transformations.

The human ability to use different tools demonstrates our capability of forming and maintaining multiple, context specific motor memories. Experimentally, this ability has been investigated in dual adaptation, where participants adjust their reaching movements to opposing visuomotor transformations. Adaptation in these paradigms occurs by distinct processes, i.e. the development of explicit aiming strategies for each transformation and/or the implicit acquisition of distinct visuomotor mappings. The presence of distinct, transformation-dependent aftereffects has been interpreted as support for the latter. Alternatively, however, distinct aftereffects could reflect adaptation of a single visuomotor map, which is locally adjusted in different regions of the workspace. Indeed, recent studies suggest that explicit aiming strategies direct where in the workspace implicit adaptation occurs.\n\nDisentangling these possibilities is critical to understanding how humans acquire and maintain separate motor memories for different skills and tools. We therefore investigated generalization of explicit and implicit adaptation to different directions after participants practiced two opposing cursor rotations, which were associated with separate visual workspaces. Whereas participants learned to compensate opposing rotations by explicit strategies that were specific to the visual workspace cue, aftereffects were not sensitive to visual workspace cues. Instead, aftereffects displayed bimodal generalization patterns that appeared to reflect locally limited learning of both transformations. By varying target arrangements and instructions, we show that these generalization patterns are consistent with implicit adaptation that generalizes locally around (explicit) movement plans associated with opposing visuomotor transformations. Our findings show that strategies can shape implicit adaptation in a complex manner.\n\nNew & NoteworthyVisuomotor dual adaptation experiments have identified contextual cues that enable learning of separate visuomotor mappings, but little is known about the underlying representations of learning. We report that visual workspace separation as a contextual cue enables participants to compensate opposing cursor rotations by a combination of explicit and implicit processes: Learners developed context-dependent explicit aiming strategies while an implicit visuomotor map represented dual adaptation independent from context by local adaptation around the explicit movement plan.

neuroscience↗

bioRxiv2018

Relative sensitivity of explicit re-aiming and implicit motor adaptation

It has become increasingly clear that learning in visuomotor rotation tasks, which induce an angular mismatch between movements of the hand and visual feedback, largely results from the combined effort of two distinct processes: implicit motor adaptation and explicit re-aiming. However, it remains unclear how these two processes work together to produce trial-by-trial learning. Previous work has found that implicit motor adaptation operates automatically, regardless of task relevancy, and saturates for large errors. In contrast, little is known about the automaticity of explicit re-aiming and its sensitivity to error magnitude. Here we sought to characterize the automaticity and sensitivity function of these two processes to determine how they work together to facilitate performance in a visuomotor rotation task. We found that implicit adaptation scales relative to the visual error, but only for small perturbations - replicating prior work. In contrast, explicit re-aiming scales linearly for all tested perturbation sizes. Furthermore, the consistency of the perturbation appears to diminish both implicit adaptation and explicit re-aiming, but to different degrees. Whereas implicit adaptation always displayed a response to the error, explicit re-aiming was only engaged when errors displayed a minimal degree of consistency. This comports with the idea that implicit adaptation is obligatory and less flexible, while explicit re-aiming is volitional and flexible.

neuroscience↗

bioRxiv2018

Dissociable Roles for Working Memory in Sensorimotor Learning

The computations underlying cognitive strategies in sensorimotor learning are poorly understood. Here we investigate such strategies in a sensorimotor transformation task. We show that strategies assume two forms, reflecting distinct working memory representations: discrete response caching of stimulus-response contingencies (e.g., look-up table; RC), and time-consuming parametric computations (e.g. mental rotation; MR). Subjects reaction times and errors suggest that both strategies are employed during learning, and trade off based on the progress of learning and the complexity of the task. Experiments using pressured preparation time support these working memory mechanisms: In discrete RC, time pressure elicits bimodal distributions of movements, in agreement with cached responses; in parametric MR, time pressure elicits a shifting distribution producing intermediate movements between visual targets and distal goals, consistent with analog re-computing of a movement plan. These results provide a specific model of working memory contributions to motor learning.

neuroscience↗

bioRxiv2017

The Cerebellum Does More Than Sensory-Prediction-Error-Based Learning In Sensorimotor Adaptation Tasks

Individuals with damage to the cerebellum perform poorly in sensorimotor adaptation paradigms. This deficit has been attributed to impairment in sensory-prediction-error-based updating of an internal forward model, a form of implicit learning. These individuals can, however, successfully counter a perturbation when instructed with an explicit aiming strategy. This successful use of an instructed aiming strategy presents a paradox: In adaptation tasks, why dont individuals with cerebellar damage come up with an aiming solution on their own to compensate for their implicit learning deficit? To explore this question, we employed a variant of a visuomotor rotation task in which, prior to executing a movement on each trial, the participants verbally reported their intended aiming location. Compared to healthy controls, participants with spinocerebellar ataxia (SCA) displayed impairments in both implicit learning and aiming. This was observed when the visuomotor rotation was introduced abruptly (Exp. 1) or gradually (Exp. 2). This dual deficit does not appear to be related to the increased movement variance associated with ataxia: Healthy undergraduates showed little change in implicit learning or aiming when their movement feedback was artificially manipulated to produce similar levels of variability (Exp. 3). Taken together the results indicate that a consequence of cerebellar dysfunction is not only impaired sensory-prediction-error-based learning, but also a difficulty in developing and/or maintaining an aiming solution in response to a visuomotor perturbation. We suggest that this dual deficit can be explained by the cerebellum forming part of a network that learns and maintains action-outcome associations across trials.\n\nNew and noteworthyIndividuals with cerebellar pathology are impaired in sensorimotor adaptation. This deficit has been attributed to an impairment in error-based learning, specifically, from a deficit in using sensory prediction errors to update an internal model. Here, we show that these individuals also have difficulty in discovering an aiming solution to overcome their adaptation deficit, suggesting a new role for the cerebellum in sensorimotor adaptation tasks.

neuroscience↗

bioRxiv2017

The C-Terminal Domain Of ParB Is Critical For Dynamic DNA Binding And Bridging Interactions Which Condense The Bacterial Centromere

The ParB protein forms DNA bridging interactions around parS to form networks which condense DNA and earmark the bacterial chromosome for segregation. The mechanism underlying the formation of ParB nucleoprotein complexes is unclear. We show here that the central DNA binding domain is essential for anchoring at parS, and that this interaction is not required for DNA condensation. Structural analysis of the C-terminal domain reveals a dimer with a lysine-rich surface that binds DNA non-specifically and is essential for DNA condensation in vitro. Mutation of either the dimerisation or the DNA binding interface eliminates ParB foci formation in vivo. Moreover, the free C-terminal domain can rapidly decondense ParB networks independently of its ability to bind DNA. Our work reveals a dual role for the C-terminal domain of ParB as both a DNA binding and bridging interface, and highlights the dynamic nature of ParB networks.

biochemistry↗

bioRxiv2017

Auditory prediction errors as individual biomarkers of schizophrenia

Schizophrenia is a complex psychiatric disorder, typically diagnosed through symptomatic evidence collected through patient interview. We aim to develop an objective biologically-based computational tool which aids diagnosis and relies on accessible imaging technologies such as electroencephalography (EEG). To achieve this, we used machine learning techniques and a combination of paradigms designed to elicit prediction errors or Mismatch Negativity (MMN) responses. MMN, an EEG component elicited by unpredictable changes in sequences of auditory stimuli, has previously been shown to be reduced in people with schizophrenia and this is arguably one of the most reproducible neurophysiological markers of schizophrenia.\n\nEEG data were acquired from 21 patients with schizophrenia and 22 healthy controls whilst they listened to three auditory oddball paradigms comprising sequences of tones which deviated in 10% of trials from regularly occurring standard tones. Deviant tones shared the same properties as standard tones, except for one physical aspect: 1) duration-the deviant stimulus was twice the duration of the standard; 2) monaural gap-deviants had a silent interval omitted from the standard, or 3) inter-aural timing difference, which caused the deviant location to be perceived as 90{degrees} away from the standards.\n\nWe used multivariate pattern analysis, a machine learning technique implemented in the Pattern Recognition for Neuroimaging Toolbox (PRoNTo) to classify images generated through statistical parametric mapping (SPM) of spatiotemporal EEG data, i.e. event-related potentials measured on the two-dimensional surface of the scalp over time. Using support vector machine (SVM) and Gaussian processes classifiers (GPC), we were able classify individual patients and controls with balanced accuracies of up to 80.48% (p-values = 0.0326, FDR corrected) and an ROC analysis yielding an AUC of 0.87. Crucially, a GPC regression revealed that MMN predicted global assessment of functioning (GAF) scores (correlation = 0.73, R2 = 0.53, p = 0.0006)

neuroscience↗