Correction: Reach adaption to a visuomotor gain with terminal error feedback involves reinforcement learning.

[This corrects the article DOI: 10.1371/journal.pone.0269297.].

Adaptation of the gain of the corrective lifting response in object manipulation transfers across the hand.

Our ability to skillfully manipulate objects is supported by rapid corrective responses that are initiated when we experience perturbations that interfere with movement goals. For example, the corrective lifting response is triggered when an object is heavier than expected and fails to lift off the surface. In this situation, the absence of expected sensory feedback signalling lift off initiates, within ~ 90 ms, an increase in lifting force. Importantly, when people repeatedly lift an object that, on occasional catch trials, is heavier than expected, the gain of the corrective response, defined as the rate of force increase, adapts to the 'catch' weight. In the present study, we investigated whether this response adaption transfers intermanually. In the training phase, participants used either their left or right hand (counterbalanced) to repeatedly lift a 3 N object that unexpectedly increased to 9 N on catch trials, leading to an increase in the gain of the lifting response across catch trials. Participants then lifted the object with their other hand. On the first catch trial, the gain remained elevated and thus transferred across the hands. This finding suggests that the history of lifts performed by one hand updates the corrective responses for both hands.

Improved accuracy and robustness of electron density profiles from JET's X-mode frequency-modulated continuous-wave reflectometers.

JET's frequency-modulated continuous wave (FMCW) reflectometers have been operating well with the current design since 2005, and density profiles have been automatically calculated intershot since then. However, the calculated profiles had long suffered from several shortcomings: poor agreement with other diagnostics, sometimes inappropriately moving radially by several centimeters, elevated levels of radial jitter, and persistent wriggles (strong unphysical oscillations). In this research, several techniques are applied to the reflectometry data analysis, and the shortcomings are significantly improved. Starting with improving the equilibrium reconstruction that estimates the background magnetic field, adding a ripple correction in the reconstructed magnetic field profile, and adding new inner-wall reflection positions estimated through ray-tracing, these changes not only improve the agreement of reconstructed profiles to other diagnostics but also solve density profile wriggles that were present during band transitions. Other smaller but also persistent wriggles were also suppressed by applying a localized correction to the measured beat frequency where persistent oscillations are present. Finally, the burst analysis method, as introduced by Varela et al. [Nucl. Fusion 46 S693 (2006)], has been implemented to extract the beat frequency from stacked spectrograms. Due to the strong suppression of spurious reflections, the radial jitter that sometimes would span several centimeters has been strongly reduced. The stacking of spectrograms has also been shown to be very useful for stacking recurring events, like small gas puff modulations, and extracting transport coefficients that would otherwise be below the noise level.

Adipokine secretion and lipolysis following gender-affirming treatment in transgender individuals.

BACKGROUND: The organ-specific effects of gender-affirming sex hormone treatment (GAHT) in transgender women (TW) and transgender men (TM) are insufficiently explored. This study investigated the effects of GAHT on adipose tissue function. METHODS: In a single-center interventional prospective study, 32 adults undergoing GAHT, 15 TW and 17 TM, were examined with anthropometry and abdominal subcutaneous adipose tissue biopsies obtained before initiation of treatment, 1 month after endogenous sex hormone inhibition and three and 11 months after initiated GAHT. Fat cell size, basal/stimulated lipolysis and cytokine secretion in adipose tissue were analyzed. RESULTS: TW displayed an increase in complement component 3a and retinol-binding protein 4 (RBP4) secretion after sex hormone inhibition, which returned to baseline following estradiol treatment. No changes in lipolysis were seen in TW. TM showed downregulation of RBP4 after treatment, but no changes in basal lipolysis. In TM, the estrogen suppression led to higher noradrenaline stimulated (NA) lipolysis that was normalized following testosterone treatment. At 11 months, the ratio of NA/basal lipolysis was lower compared to baseline. There were no significant changes in fat cell size in either TW or TM. CONCLUSION: In TW, gonadal hormone suppression results in transient changes in cytokines and in TM there are some changes in NA-stimulated lipolysis following testosterone treatment. However, despite the known metabolic effects of sex hormones, the overall effects of GAHT on adipose tissue function are small and likely have limited clinical relevance, but larger studies with longer follow-up are needed to confirm these findings. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02518009, Retrospectively registered 7 August 2015.

Weight loss outcomes are generally worse for dogs and cats with class II obesity, defined as > 40% overweight.

In pet dogs and cats, adiposity is most-often estimated clinically using a 9-category body condition score (BCS), with BCS 9 equating to ~ 40% overweight. Animals that are more overweight (> 40%) are seen in clinical practice but are not appropriately depicted by descriptions in the existing categories. To determine whether being > 40% overweight has clinical relevance, this study aimed to compare the outcomes of weight management in animals that were > 40% overweight with those < 40% overweight. Records of dogs and cats attending a specialist obesity care clinic, where adiposity is determined using dual-energy X-ray absorptiometry (DXA), were reviewed. Animals were assigned to two classes (class I ≤ 40% overweight: 118/398 [40%] dogs and 68/116 [59%] cats; class II, > 40% overweight: 180/398 [60%] dogs and 48/116 [41%] cats) based on DXA results, and weight loss outcomes were compared. Fewer class II dogs obesity completed weight management than class I dogs (P < 0.001), rate of weight loss was also slower (P = 0.012) and lean tissue loss greater (P < 0.001). Compared with class I, cats with class II obesity lost more weight (P = 0.048) albeit over a longer period (P = 0.043) leading to greater lean tissue loss (P = 0.004). Approximately half the pets presenting to a specialist clinic were have class II obesity (> 40% overweight), and some weight loss outcomes are worse for these animals.

Interaction between decision-making and motor learning when selecting reach targets in the presence of bias and noise.

Motor errors can have both bias and noise components. Bias can be compensated for by adaptation and, in tasks in which the magnitude of noise varies across the environment, noise can be reduced by identifying and then acting in less noisy regions of the environment. Here we examine how these two processes interact when participants reach under a combination of an externally imposed visuomotor bias and noise. In a center-out reaching task, participants experienced noise (zero-mean random visuomotor rotations) that was target-direction dependent with a standard deviation that increased linearly from a least-noisy direction. They also experienced a constant bias, a visuomotor rotation that varied (across groups) from 0 to 40 degrees. Critically, on each trial, participants could select one of three targets to reach to, thereby allowing them to potentially select targets close to the least-noisy direction. The group who experienced no bias (0 degrees) quickly learned to select targets close to the least-noisy direction. However, groups who experienced a bias often failed to identify the least-noisy direction, even though they did partially adapt to the bias. When noise was introduced after participants experienced and adapted to a 40 degrees bias (without noise) in all directions, they exhibited an improved ability to find the least-noisy direction. We developed two models-one for reach adaptation and one for target selection-that could explain participants' adaptation and target-selection behavior. Our data and simulations indicate that there is a trade-off between adaptation and selection. Specifically, because bias learning is local, participants can improve performance, through adaptation, by always selecting targets that are closest to a chosen direction. However, this comes at the expense of improving performance, through selection, by reaching toward targets in different directions to find the least-noisy direction.

Fast Feedback Responses to Categorical Sensorimotor Errors That Do Not Indicate Error Magnitude Are Optimized Based on Short- and Long-Term Memory.

Skilled motor performance depends critically on rapid corrective responses that act to preserve the goal of the movement in the face of perturbations. Although it is well established that the gain of corrective responses elicited while reaching toward objects adapts to different contexts, little is known about the adaptability of corrective responses supporting the manipulation of objects after they are grasped. Here, we investigated the adaptability of the corrective response elicited when an object being lifted is heavier than expected and fails to lift off when predicted. This response involves a monotonic increase in vertical load force triggered, within ∼90 ms, by the absence of expected sensory feedback signaling lift off and terminated when actual lift off occurs. Critically, because the actual weight of the object cannot be directly sensed at the moment the object fails to lift off, any adaptation of the corrective response would have to be based on memory from previous lifts. We show that when humans, including men and women, repeatedly lift an object that on occasional catch trials increases from a baseline weight to a fixed heavier weight, they scale the gain of the response (i.e., the rate of force increase) to the heavier weight within two to three catch trials. We also show that the gain of the response scales, on the first catch trial, with the baseline weight of the object. Thus, the gain of the lifting response can be adapted by both short- and long-term experience. Finally, we demonstrate that this adaptation preserves the efficacy of the response across contexts.SIGNIFICANCE STATEMENT Here, we present the first investigation of the adaptability of the corrective lifting response elicited when an object is heavier than expected and fails to lift off when predicted. A striking feature of the response, which is driven by a sensory prediction error arising from the absence of expected sensory feedback, is that the magnitude of the error is unknown. That is, the motor system only receives a categorical error indicating that the object is heavier than expected but not its actual weight. Although the error magnitude is not known at the moment the response is elicited, we show that the response can be scaled to predictions of error magnitude based on both recent and long-term memories.

Visual search for reach targets in actionable space is influenced by movement costs imposed by obstacles.

Real world search tasks often involve action on a target object once it has been located. However, few studies have examined whether movement-related costs associated with acting on located objects influence visual search. Here, using a task in which participants reached to a target object after locating it, we examined whether people take into account obstacles that increase movement-related costs for some regions of the reachable search space but not others. In each trial, a set of 36 objects (4 targets and 32 distractors) were displayed on a vertical screen and participants moved a cursor to a target after locating it. Participants had to fixate on an object to determine whether it was a target or distractor. A rectangular obstacle, of varying length, location, and orientation, was briefly displayed at the start of the trial. Participants controlled the cursor by moving the handle of a robotic manipulandum in a horizontal plane. The handle applied forces to simulate contact between the cursor and the unseen obstacle. We found that search, measured using eye movements, was biased to regions of the search space that could be reached without moving around the obstacle. This result suggests that when deciding where to search, people can incorporate the physical structure of the environment so as to reduce the movement-related cost of subsequently acting on the located target.

Memory, perceptual, and motor costs affect the strength of categorical encoding during motor learning of object properties.

Nearly all tasks of daily life involve skilled object manipulation, and successful manipulation requires knowledge of object dynamics. We recently developed a motor learning paradigm that reveals the categorical organization of motor memories of object dynamics. When participants repeatedly lift a constant-density "family" of cylindrical objects that vary in size, and then an outlier object with a greater density is interleaved into the sequence of lifts, they often fail to learn the weight of the outlier, persistently treating it as a family member despite repeated errors. Here we examine eight factors (Similarity, Cardinality, Frequency, History, Structure, Stochasticity, Persistence, and Time Pressure) that could influence the formation and retrieval of category representations in the outlier paradigm. In our web-based task, participants (N = 240) anticipated object weights by stretching a virtual spring attached to the top of each object. Using Bayesian t-tests, we analyze the relative impact of each manipulated factor on categorical encoding (strengthen, weaken, or no effect). Our results suggest that category representations of object weight are automatic, rigid, and linear and, as a consequence, the key determinant of whether an outlier is encoded as a member of the family is its discriminability from the family members.

The influence of movement-related costs when searching to act and acting to search.

Real-world search behavior often involves limb movements, either during search or after search. Here we investigated whether movement-related costs influence search behavior in two kinds of search tasks. In our visual search tasks, participants made saccades to find a target object among distractors and then moved a cursor, controlled by the handle of a robotic manipulandum, to the target. In our manual search tasks, participants moved the cursor to perform the search, placing it onto objects to reveal their identity as either a target or a distractor. In all tasks, there were multiple targets. Across experiments, we manipulated either the effort or time costs associated with movement such that these costs varied across the search space. We varied effort by applying different resistive forces to the handle, and we varied time costs by altering the speed of the cursor. Our analysis of cursor and eye movements during manual and visual search, respectively, showed that effort influenced manual search but did not influence visual search. In contrast, time costs influenced both visual and manual search. Our results demonstrate that, in addition to perceptual and cognitive factors, movement-related costs can also influence search behavior.NEW & NOTEWORTHY Numerous studies have investigated the perceptual and cognitive factors that influence decision making about where to look, or move, in search tasks. However, little is known about how search is influenced by movement-related costs associated with acting on an object once it has been visually located or acting during manual search. In this article, we show that movement time costs can bias visual and manual search and that movement effort costs bias manual search.

Whole-brain dynamics of human sensorimotor adaptation.

Humans vary greatly in their motor learning abilities, yet little is known about the neural processes that underlie this variability. We identified distinct profiles of human sensorimotor adaptation that emerged across 2 days of learning, linking these profiles to the dynamics of whole-brain functional networks early on the first day when cognitive strategies toward sensorimotor adaptation are believed to be most prominent. During early learning, greater recruitment of a network of higher-order brain regions, involving prefrontal and anterior temporal cortex, was associated with faster learning. At the same time, greater integration of this "cognitive network" with a sensorimotor network was associated with slower learning, consistent with the notion that cognitive strategies toward adaptation operate in parallel with implicit learning processes of the sensorimotor system. On the second day, greater recruitment of a network that included the hippocampus was associated with faster learning, consistent with the notion that declarative memory systems are involved with fast relearning of sensorimotor mappings. Together, these findings provide novel evidence for the role of higher-order brain systems in driving variability in adaptation.

Object weight can be rapidly predicted, with low cognitive load, by exploiting learned associations between the weights and locations of objects.

Weight prediction is critical for dexterous object manipulation. Previous work has focused on lifting objects presented in isolation and has examined how the visual appearance of an object is used to predict its weight. Here we tested the novel hypothesis that when interacting with multiple objects, as is common in everyday tasks, people exploit the locations of objects to directly predict their weights, bypassing slower and more demanding processing of visual properties to predict weight. Using a three-dimensional robotic and virtual reality system, we developed a task in which participants were presented with a set of objects. In each trial a randomly chosen object translated onto the participant's hand and they had to anticipate the object's weight by generating an equivalent upward force. Across conditions we could control whether the visual appearance and/or location of the objects were informative as to their weight. Using this task, and a set of analogous web-based experiments, we show that when location information was predictive of the objects' weights participants used this information to achieve faster prediction than observed when prediction is based on visual appearance. We suggest that by "caching" associations between locations and weights, the sensorimotor system can speed prediction while also lowering working memory demands involved in predicting weight from object visual properties.NEW & NOTEWORTHY We use a novel object support task using a three-dimensional robotic interface and virtual reality system to provide evidence that the locations of objects are used to predict their weights. Using location information, rather than the visual appearance of the objects, supports fast prediction, thereby avoiding processes that can be demanding on working memory.

Distinct patterns of cortical manifold expansion and contraction underlie human sensorimotor adaptation.

Sensorimotor learning is a dynamic, systems-level process that involves the combined action of multiple neural systems distributed across the brain. Although much is known about the specialized cortical systems that support specific components of action (such as reaching), we know less about how cortical systems function in a coordinated manner to facilitate adaptive behavior. To address this gap, our study measured human brain activity using functional MRI (fMRI) while participants performed a classic sensorimotor adaptation task and used a manifold learning approach to describe how behavioral changes during adaptation relate to changes in the landscape of cortical activity. During early adaptation, areas in the parietal and premotor cortices exhibited significant contraction along the cortical manifold, which was associated with their increased covariance with regions in the higher-order association cortex, including both the default mode and fronto-parietal networks. By contrast, during Late adaptation, when visuomotor errors had been largely reduced, a significant expansion of the visual cortex along the cortical manifold was associated with its reduced covariance with the association cortex and its increased intraconnectivity. Lastly, individuals who learned more rapidly exhibited greater covariance between regions in the sensorimotor and association cortices during early adaptation. These findings are consistent with a view that sensorimotor adaptation depends on changes in the integration and segregation of neural activity across more specialized regions of the unimodal cortex with regions in the association cortex implicated in higher-order processes. More generally, they lend support to an emerging line of evidence implicating regions of the default mode network (DMN) in task-based performance.

Spontaneous Behavioural Recovery Following Stroke Relates to the Integrity of Parietal and Temporal Regions.

Stroke is a devastating disease that results in neurological deficits and represents a leading cause of death and disability worldwide. Following a stroke, there is a degree of spontaneous recovery of function, the neural basis of which is of great interest among clinicians in their efforts to reduce disability following stroke and enhance rehabilitation. Conventionally, work on spontaneous recovery has tended to focus on the neural reorganization of motor cortical regions, with comparably little attention being paid to changes in non-motor regions and how these relate to recovery. Here we show, using structural neuroimaging in a macaque stroke model (N = 31) and by exploiting individual differences in spontaneous behavioural recovery, that the preservation of regions in the parietal and temporal cortices predict animal recovery. To characterize recovery, we performed a clustering analysis using Non-Human Primate Stroke Scale (NHPSS) scores and identified a good versus poor recovery group. By comparing the preservation of brain volumes in the two groups, we found that brain areas in integrity of brain areas in parietal, temporal and somatosensory cortex were associated with better recovery. In addition, a decoding approach performed across all subjects revealed that the preservation of specific brain regions in the parietal, somatosensory and medial frontal cortex predicted recovery. Together, these findings highlight the importance of parietal and temporal regions in spontaneous behavioural recovery.

The effect of obesity and subsequent weight reduction on cardiac structure and function in dogs.

BACKGROUND: In people, the cardiovascular effects of obesity include systemic hypertension, cardiac remodelling and both systolic and diastolic dysfunction, whilst weight reduction can reverse myocardial remodelling and reduce risk of subsequent cardiovascular disease. To date, variable results are reported in studies of the effect of obesity and controlled weight reduction on cardiovascular morphology and function in dogs. This prospective study aimed to assess cardiac function, heart rate variability, cardiac biomarkers and body composition before and after weight reduction in pet dogs with obesity. Twenty-four client-owned dogs referred for weight management due to obesity were recruited. To assess the cardiac effects of obesity, body composition analysis (by dual energy X-ray absorptiometry, DEXA) and cardiovascular assessment (echocardiography, Doppler blood pressure, electrocardiography, cardiac biomarkers) were performed prior to weight management. Twelve dogs completed the study and reached target weight, receiving a further cardiovascular assessment and DEXA. A Wilcoxon-signed rank test was used to compare each variable pre- and post- weight reduction. RESULTS: Median (interquartile range) duration of weight loss was 224 days (124-245 days), percentage weight loss was 23% (18-31%) of starting weight. Median change in body fat mass was -50% (-44% to -55%; P = 0.004), whilst median change in lean mass was -7% (+ 1% to -18%, P = 0.083). Before weight reduction, diastolic dysfunction (evidence of impaired relaxation in all dogs), increased left ventricular wall thickness and mildly elevated systolic blood pressure (14/24 ≥ 160 mmHg, median 165 mmHg (140-183)) were common features in dogs with obesity. However, systolic left ventricular wall dimensions were the only variables that changed after weight reduction, with a decrease in both the systolic interventricular septum (P = 0.029) and systolic left ventricular free wall (P = 0.017). There was no evidence of decreased heart rate variability in dogs with obesity (P = 0.367), and no change in cardiac biomarker concentrations with weight reduction (N-terminal proBNP, P = 0.262; cardiac troponin I P = 0.657). CONCLUSIONS: Canine obesity results in diastolic dysfunction and left ventricular hypertrophy, the latter of which improves with significant weight and fat mass reduction. Further studies are required to clarify the clinical consequences of these findings.

Reach adaption to a visuomotor gain with terminal error feedback involves reinforcement learning.

Motor adaptation can be achieved through error-based learning, driven by sensory prediction errors, or reinforcement learning, driven by reward prediction errors. Recent work on visuomotor adaptation has shown that reinforcement learning leads to more persistent adaptation when visual feedback is removed, compared to error-based learning in which continuous visual feedback of the movement is provided. However, there is evidence that error-based learning with terminal visual feedback of the movement (provided at the end of movement) may be driven by both sensory and reward prediction errors. Here we examined the influence of feedback on learning using a visuomotor adaptation task in which participants moved a cursor to a single target while the gain between hand and cursor movement displacement was gradually altered. Different groups received either continuous error feedback (EC), terminal error feedback (ET), or binary reinforcement feedback (success/fail) at the end of the movement (R). Following adaptation we tested generalization to targets located in different directions and found that generalization in the ET group was intermediate between the EC and R groups. We then examined the persistence of adaptation in the EC and ET groups when the cursor was extinguished and only binary reward feedback was provided. Whereas performance was maintained in the ET group, it quickly deteriorated in the EC group. These results suggest that terminal error feedback leads to a more robust form of learning than continuous error feedback. In addition our findings are consistent with the view that error-based learning with terminal feedback involves both error-based and reinforcement learning.

Neural excursions from manifold structure explain patterns of learning during human sensorimotor adaptation.

Humans vary greatly in their motor learning abilities, yet little is known about the neural mechanisms that underlie this variability. Recent neuroimaging and electrophysiological studies demonstrate that large-scale neural dynamics inhabit a low-dimensional subspace or manifold, and that learning is constrained by this intrinsic manifold architecture. Here, we asked, using functional MRI, whether subject-level differences in neural excursion from manifold structure can explain differences in learning across participants. We had subjects perform a sensorimotor adaptation task in the MRI scanner on 2 consecutive days, allowing us to assess their learning performance across days, as well as continuously measure brain activity. We find that the overall neural excursion from manifold activity in both cognitive and sensorimotor brain networks is associated with differences in subjects' patterns of learning and relearning across days. These findings suggest that off-manifold activity provides an index of the relative engagement of different neural systems during learning, and that subject differences in patterns of learning and relearning are related to reconfiguration processes occurring in cognitive and sensorimotor networks.

Human Variation in Error-Based and Reinforcement Motor Learning Is Associated With Entorhinal Volume.

Error-based and reward-based processes are critical for motor learning and are thought to be mediated via distinct neural pathways. However, recent behavioral work in humans suggests that both learning processes can be bolstered by the use of cognitive strategies, which may mediate individual differences in motor learning ability. It has been speculated that medial temporal lobe regions, which have been shown to support motor sequence learning, also support the use of cognitive strategies in error-based and reinforcement motor learning. However, direct evidence in support of this idea remains sparse. Here we first show that better overall learning during error-based visuomotor adaptation is associated with better overall learning during the reward-based shaping of reaching movements. Given the cognitive contribution to learning in both of these tasks, these results support the notion that strategic processes, associated with better performance, drive intersubject variation in both error-based and reinforcement motor learning. Furthermore, we show that entorhinal cortex volume is larger in better learning individuals-characterized across both motor learning tasks-compared with their poorer learning counterparts. These results suggest that individual differences in learning performance during error and reinforcement learning are related to neuroanatomical differences in entorhinal cortex.

Motor memories of object dynamics are categorically organized.

The ability to predict the dynamics of objects, linking applied force to motion, underlies our capacity to perform many of the tasks we carry out on a daily basis. Thus, a fundamental question is how the dynamics of the myriad objects we interact with are organized in memory. Using a custom-built three-dimensional robotic interface that allowed us to simulate objects of varying appearance and weight, we examined how participants learned the weights of sets of objects that they repeatedly lifted. We find strong support for the novel hypothesis that motor memories of object dynamics are organized categorically, in terms of families, based on covariation in their visual and mechanical properties. A striking prediction of this hypothesis, supported by our findings and not predicted by standard associative map models, is that outlier objects with weights that deviate from the family-predicted weight will never be learned despite causing repeated lifting errors.

Maintenance energy requirements in cats following controlled weight loss: An observational study.

There is a paucity of information regarding the phenomenon of weight regain after successful weight reduction in cats. This study aimed to estimate post-weight reduction maintenance energy requirements (MER) required to maintain stable weight in a group of pet cats. Nineteen cats that had successfully completed a controlled weight reduction programme were enrolled. For inclusion, at least 2 months of follow-up had to be available for review, and the maximum change in weight during maintenance was ±2%. Post-weight-reduction MER was estimated by determining dietary energy consumption from owner diary records. The Friedman test was used to compare bodyweight and energy intake at different stages of weight management. Simple and multiple linear regression were used to identify factors associated with post-weight-reduction MER. The median (interquartile range) duration of weight maintenance was 179 days (119-408 days) and, during this time, MER was 273 ± 56.7 kJ per kg0.67 ideal bodyweight (IBW) per day. Post-weight-reduction MER was greater than metabolisable energy intake at the end (233 ± 29.5 kJ IBW per kg0.67 per day; P < 0.001) but not the start (255 ± 38.6 kJ per kg0.67 IBW per day; P = 0.148) of the weight reduction period. Using simple and multiple linear regression, the only variable that was associated with post-weight reduction MER was the mean ME intake during weight reduction (r2 = 0.349, P = 0.008). Post-weight-reduction MER at the lower limits of MER recommendations for pet cats might predispose to weight regain during the weight maintenance phase.