Lee A. Baugh

Material evidence: interaction of well-learned priors and sensorimotor memory when lifting objects

Skilled object lifting requires the prediction of object weight. When lifting new objects, such prediction is based on well-learned size-weight and material-density correlations, or priors. However, if the prediction is erroneous, people quickly learn the weight of the particular object and can use this knowledge, referred to as sensorimotor memory, when lifting the object again. In the present study, we explored how sensorimotor memory, gained when lifting a given object, interacts with well-learned material-density priors when predicting the weight of a larger but otherwise similar-looking object. Different groups of participants 1st lifted 1 of 4 small objects 10 times. These included a pair of wood-filled objects and a pair of brass-filled objects where 1 of each pair was covered in a wood veneer and the other was covered in a brass veneer. All groups then lifted a larger, brass-filled object with the same covering as the small object they had lifted. For each lift, we determined the initial peak rate of change of vertical load-force rate and the load-phase duration, which provide estimates of predicted object weight. Analysis of the 10th lift of the small cube revealed no effects of surface material, indicating participants learned the appropriate forces required to lift the small cube regardless of object appearance. However, both surface material and core material of the small cube affected the 1st lift of the large block. We conclude that sensorimotor memory related to object density can contribute to weight prediction when lifting novel objects but also that long-term priors related to material properties can influence the prediction.

Simultaneous encoding of the direction and orientation of potential targets during reach planning: evidence of multiple competing reach plans

Reaches performed in many natural situations involve selecting a specific target from a number of alternatives. Recent studies show that before reaching, multiple potential reach targets are encoded in brain regions involved in action control and that, when people are required to initiate the reach before the target is specified, initial hand direction is biased by the spatial distribution of potential targets. These findings have led to the suggestion that the brain, during planning, simultaneously prepares multiple reaches to potential targets. In addition to hand direction, reach planning often involves specifying other parameters such as wrist orientation. For example, when posting a letter in a mail slot, both the location and orientation of the slot must be encoded to control hand direction and orientation. Therefore, if the brain prepares multiple reaches to potential targets and if these targets require the specification of hand direction and orientation, then both of these variables should be biased by the spatial distribution of potential targets. To test this prediction, we examined a task in which participants moved a hand-held rectangular tool toward multiple rectangular targets of varying location and orientation, one of which was selected, with equal probability as the actual target after movement initiation. We found that initial hand direction and orientation were biased by the spatial distributions of potential target locations and orientations, respectively. This result is consistent with the idea that the brain, in cases of target uncertainty, simultaneously plans fully specified reaching movements to all potential targets.

Novel claustrum activation observed during a visuomotor adaptation task using a viewing window paradigm

Previous literature has reported a wide range of anatomical correlates when participants are required to perform a visuomotor adaptation task. However, traditional adaptation tasks suffer a number of inherent limitations that may, in part, give rise to this variability. For instance, the sparse visual environment does not map well onto conditions in which a visuomotor transformation would normally be required in everyday life. To further clarify these neural underpinnings, functional magnetic resonance imaging (fMRI) was performed on 17 (6M, age range 20-45 years old; mean age=26) naive participants performing a viewing window task in which a visuomotor transformation was created by varying the relationship between the participants movement and the resultant movement of the viewing window. The viewing window task more naturally replicates scenarios in which haptic and visual information would be combined to achieve a higher-level goal. Even though activity related to visuomotor adaptation was found within previously reported regions of the parietal lobes, frontal lobes, and occipital lobes, novel activation patterns were observed within the claustrum - a region well-established as multi-modal convergence zone. These results confirm the diversity in the number and location of neurological systems recruited to perform a required visuomotor adaptation, and provide the first evidence of participation of the claustrum to overcome a visuomotor transformation.

When What's Left Is Right: Visuomotor Transformations in an Aged Population

Background There has been little consensus as to whether age-related visuomotor adaptation effects are readily observable. Some studies have found slower adaptation, and/or reduced overall levels. In contrast, other methodologically similar studies have found no such evidence of aging effects on visuomotor adaptation. A crucial early step in successful adaptation is the ability to perform the necessary transformation to complete the task at hand. The present study describes the use of a viewing window paradigm to examine the effects of aging in a visuomotor transformation task. Methods Two groups of participants, a young adult control group (age range 18–33 years old, mean age = 22) and an older adult group (age range 62–74, mean age = 68) completed a viewing window task that was controlled by the user via a computer touchscreen. Four visuomotor “flip” conditions were created by varying the relationship between the participants movement, and the resultant on-screen movement of the viewing window: 1) No flip 2) X-Axis and Y-axis body movements resulted in the opposite direction of movement of the viewing window. In each of the 3) Flip-X and 4) Flip-Y conditions, the solitary X- or Y-axes were reversed. Response times and movement of the window were recorded. Conclusions Older participants demonstrated impairments in performing a required visuomotor transformation, as evidenced by more complex scanning patterns and longer scanning times when compared to younger control participants. These results provide additional evidence that the mechanisms involved in visuomotor transformation are negatively affected by age.

Hand-held tools with complex kinematics are efficiently incorporated into movement planning and online control

Certain hand-held tools alter the mapping between hand motion and motion of the tool end point that must be controlled in order to perform a task. For example, when using a pool cue, the motion of the cue tip is reversed relative to the hand. Previous studies have shown that the time required to initiate a reaching movement (Fernandez-Ruiz J, Wong W, Armstrong IT, Flanagan JR. Behav Brain Res 219: 8-14, 2011), or correct an ongoing reaching movement (Gritsenko V, Kalaska JF. J Neurophysiol 104: 3084-3104, 2010), is prolonged when the mapping between hand motion and motion of a cursor controlled by the hand is reversed. Here we show that these time costs can be significantly reduced when the reversal is instantiated by a virtual hand-held tool. Participants grasped the near end of a virtual tool, consisting of a rod connecting two circles, and moved the end point to displayed targets. In the reversal condition, the rod translated through, and rotated about, a pivot point such that there was a left-right reversal between hand and end point motion. In the nonreversal control, the tool translated with the hand. As expected, when only the two circles were presented, movement initiation and correction times were much longer in the reversal condition. However, when full vision of the tool was provided, the reaction time cost was almost eliminated. These results indicate that tools with complex kinematics can be efficiently incorporated into sensorimotor control mechanisms used in movement planning and online control.

Representing multiple object weights: Competing priors and sensorimotor memories

When lifting an object, individuals scale lifting forces based on long-term priors relating external object properties (such as material and size) to object weight. When experiencing objects that are poorly predicted by priors, people rapidly form and update sensorimotor memories that can be used to predict an objects atypical size-weight relation in support of predictively scaling lift forces. With extensive experience in lifting such objects, long-term priors, assessed with weight judgments, are gradually updated. The aim of the present study was to understand the formation and updating of these memory processes. Participants lifted, over multiple days, a set of black cubes with a normal size-weight mapping and green cubes with an inverse size-weight mapping. Sensorimotor memory was assessed with lifting forces, and priors associated with the black and green cubes were assessed with the size-weight illusion (SWI). Interference was observed in terms of adaptation of the SWI, indicating that priors were not independently adjusted. Half of the participants rapidly learned to scale lift forces appropriately, whereas reduced learning was observed in the others, suggesting that individual differences may be affecting sensorimotor memory abilities. A follow-up experiment showed that lifting forces are not accurately scaled to objects when concurrently performing a visuomotor association task, suggesting that sensorimotor memory formation involves cognitive resources to instantiate the mapping between object identity and weight, potentially explaining the results of experiment 1 These results provide novel insight into the formation and updating of sensorimotor memories and provide support for the independent adjustment of sensorimotor memory and priors.

Cognitive attribution of the source of an error in object-lifting results in differences in motor generalization.

To lift an object, the motor system must predict the weight of the object and use this information to program appropriate lifting forces. If this prediction is erroneous, people may assign blame for the error to either themselves or an external source—a process called credit assignment. In the present study, we explored the role of credit assignment on weight predictions during a lifting task. Participants were told that the EMG surface electrodes attached to their lifting hand were either part of a “passive” system that recorded muscular activity, or part of an “active” system that would apply energy to the muscle, influencing weight perception. Participants performed 90 lifts of the training blocks, followed by 10 lifts of a newly encountered larger test block. In between training and test trials, the experimenter turned off the recording system and removed the surface electrodes for participants in the “active” group. For each lift, we determined the initial peak rate of change of vertical load force rate and load-phase duration, estimates of predicted object weight. Analysis of the first 10 training lifts and the last 10 training lifts revealed no effect of Active versus Passive EMG on weight predictions. However, after removing the EMG equipment, participants in the “active” group failed to scale their predictive load forces in the same manner as those in the “passive” condition when lifting a novel block. We conclude that cognitive information may play a role in credit assignment, influencing weight prediction when lifting novel objects.

It’s too quick to blame myself—the effects of fast and slow rates of change on credit assignment during object lifting

Although there have been substantial research efforts examining the effect of various rates of change in reaching movements, there has been little to no research devoted to this issue during object manipulation tasks. In force-field and visuomotor adaptation studies, two parallel processes have been identified: first, a fast process that adapts and de-adapts quickly is thought to enable the actor to deal with potentially transient perturbations. Second, a slower, but longer lasting process adapts if these initial perturbations persist over time. In a largely separate body of research, the role of credit assignment has been examined in terms of allotting the cause of errors to changes in the body vs. changes in the outside world. Of course, these two processes are usually linked within the real world, with short lasting perturbations most often being linked to external causes and longer lasting perturbations being linked to internal causes. Here, we demonstrate that the increases in load forces associated with a gradual increase in object weight during a natural object lifting task are transferred when lifting a novel object, whereas a sudden increase in object weight is not. We speculate that gradual rates of change in the weight of the object being lifted are attributed to the self, whereas fast rates of change are more likely to be attributed to the external environment. This study extends our knowledge of the multiple timescales involved in motor learning to a more natural object manipulation scenario, while concurrently providing support for the hypothesis that the multiple time scales involved in motor learning are tuned for different learning contexts.

Behavioural distinction between strategic control and spatial realignment during visuomotor adaptation in a viewing window task.

We must frequently adapt our movements in order to successfully perform motor tasks. These visuomotor adaptations can occur with or without our awareness and so, have generally been described by two mechanisms: strategic control and spatial realignment. Strategic control is a conscious modification used when discordance between an intended and actual movement is observed. Spatial realignment is an unconscious recalibration in response to subtle differences between an intended and efferent movement. Traditional methods of investigating visuomotor adaptation often involve simplistic, repetitive motor goals and so may be vulnerable to subject boredom or expectation. Our laboratory has recently developed a novel, engaging computer-based task, the Viewing Window, to investigate visuomotor adaptation to large, apparent distortions. Here, we contrast behavioural measures of visuomotor adaptation during the Viewing Window task when either gradual progressive rotations or large, sudden rotations are introduced in order to demonstrate that this paradigm can be utilized to investigate both strategic control and spatial realignment. The gradual rotation group demonstrated significantly faster mean velocities and spent significantly less time off the object compared to the sudden rotation group. These differences demonstrate adaptation to the distortion using spatial realignment. Scan paths revealed greater after-effects in the gradual rotation group reflected by greater time spent scanning areas off of the object. These results demonstrate the ability to investigate both strategic control and spatial realignment. Thus, the Viewing Window provides a powerful engaging tool for investigating the neural basis of visuomotor adaptation and impairment following injury and disease.

A novel integrative method for analyzing eye and hand behaviour during reaching and grasping in an MRI environment

The development of noninvasive neuroimaging techniques, such as fMRI, has rapidly advanced our understanding of the neural systems underlying the integration of visual and motor information. However, the fMRI experimental design is restricted by several environmental elements, such as the presence of the magnetic field and the restricted view of the participant, making it difficult to monitor and measure behaviour. The present article describes a novel, specialized software package developed in our laboratory called Biometric Integration Recording and Analysis (BIRA). BIRA integrates video with kinematic data derived from the hand and eye, acquired using MRI-compatible equipment. The present article demonstrates the acquisition and analysis of eye and hand data using BIRA in a mock (0 Tesla) scanner. A method for collecting and integrating gaze and kinematic data in fMRI studies on visuomotor behaviour has several advantages: Specifically, it will allow for more sophisticated, behaviourally driven analyses and eliminate potential confounds of gaze or kinematic data.