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To accurately estimate the state of the body, the nervous system needs to account for delays between signals from different sensory modalities. To investigate how such delays may be represented in the sensorimotor system, we asked human participants to play a virtual pong game in which the movement of the virtual paddle was delayed with respect to their hand movement. We tested the representation of this new mapping between the hand and the delayed paddle by examining transfer of adaptation to blind reaching and blind tracking tasks. These blind tasks enabled to capture the representation in feedforward mechanisms of movement control. A Time Representation of the delay is an estimation of the actual time lag between hand and paddle movements. A State Representation is a representation of delay using current state variables: the distance between the paddle and the ball originating from the delay may be considered as a spatial shift; the low sensitivity in the response of the paddle may be interpreted as a minifying gain; and the lag may be attributed to a mechanical resistance that influences paddles movement. We found that the effects of prolonged exposure to the delayed feedback transferred to blind reaching and tracking tasks and caused participants to exhibit hypermetric movements. These results, together with simulations of our representation models, suggest that delay is not represented based on time, but rather as a spatial gain change in visuomotor mapping.

Byline: Lior Shmuelof (Department of Neurobiology Hebrew Univeristy, Jerusalem, Israel); Ehud Zohary (Department of Neurobiology Hebrew Univeristy, Jerusalem, Israel, Interdisciplinary Center for Neural Computation Hebrew University, Jerusalem, Israel, liorsh@pob.huji.ac.il) Keywords: [...]

A variety of eye tracking studies have demonstrated that young children with ASD gaze at images and movies of social interactions differently than typically developing children. These findings have supported the hypothesis that gaze behavior differences are generated by a weaker preference for social stimuli in ASD children. The hypothesis assumes that gaze differences are not caused by abnormalities in oculomotor function including saccade frequency and kinematics. Previous studies of oculomotor function have mostly been performed with school‐age children, adolescents, and adults using visual search, anti‐saccade, and gap saccade tasks that are less suitable for young pre‐school children. Here, we examined oculomotor function in 144 children (90 with ASD and 54 controls), 1–10‐years‐old, as they watched two animated movies interleaved with the presentation of multiple salient stimuli that elicited saccades‐to‐targets. The results revealed that the number of fixations, fixation duration, number of saccades, saccade duration, saccade accuracy, and saccade latency did not differ significantly across groups. Minor initial differences in saccade peak velocity were not supported by analysis with a linear mixed model. These findings suggest that most children with ASD exhibit similar oculomotor function to that of controls, when performing saccades‐to‐targets or freely viewing child‐friendly movies. This suggests that previously reported gaze abnormalities in children with ASD are not due to underlying oculomotor deficiencies. Lay Summary This study demonstrates that children with ASD perform similar eye movements to those of controls when freely observing movies or making eye movements to targets. Similar results were apparent across groups in the number of eye movements, their accuracy, duration, and other measures that assess eye movement control. These findings are important for interpreting previously reported differences in gaze behavior of children with ASD, which are likely due to atypical social preferences rather than impaired control of eye movements. [ABSTRACT FROM AUTHOR]

When movements are perturbed in adaptation tasks, humans and other animals show incomplete compensation, tolerating small but sustained residual errors that persist despite repeated trials. State-space models explain this residual asymptotic error as interplay between learning from error and reversion to baseline, a form of forgetting. Previous work using zero-error-clamp trials has shown that reversion to baseline is not obligatory and can be overcome by manipulating feedback. We posited that novel error-clamp trials, in which feedback is constrained but has nonzero error and variance, might serve as a contextual cue for recruitment of other learning mechanisms that would then close the residual error. When error clamps were nonzero and had zero variance, human subjects changed their learning policy, using exploration in response to the residual error, despite their willingness to sustain such an error during the training block. In contrast, when the distribution of feedback in clamp trials was naturalistic, with persistent mean error but also with variance, a statespace model accounted for behavior in clamps, even in the absence of task success. Therefore, when the distribution of errors matched those during training, state-space models captured behavior during both adaptation and error-clamp trials because error-based learning dominated; when the distribution of feedback was altered, other forms of learning were triggered that did not follow the state-space model dynamics exhibited during training. The residual error during adaptation appears attributable to an error-dependent learning process that has the property of reversion toward baseline and that can suppress other forms of learning. [ABSTRACT FROM AUTHOR]

A methodology for investigating learning is developed using activation distributions, as opposed to standard voxel-level interaction tests. The approach uses tests of dimensionality to consider the ensemble of paired changes in voxel activation. The developed method allows for the investigation of non-focal and non-localized changes due to learning. In exchange for increased power to detect learning-based changes, this procedure sacrifices the localization information gained via voxel-level interaction testing. The test is demonstrated on an arc-pointing motor task for the study of motor learning, which served as the motivation for this methodological development. The proposed framework considers activation distribution, while the specific proposed test investigates linear tests of dimensionality. This paper includes: the development of the framework, a large scale simulation study, and the subsequent application to a study of motor learning in healthy adults. While the performance of the method was excellent when model assumptions held, complications arose in instances of massive numbers of null voxels or varying angles of principal dimension across subjects. Further analysis found that careful masking addressed the former concern, while an angle correction successfully resolved the latter. The simulation results demonstrated that the study of linear dimensionality is able to capture learning effects. The motivating data set used to illustrate the method evaluates two similar arc-pointing tasks, each over two sessions, with training on only one of the tasks in between sessions. The results suggests different activation distribution dimensionality when considering the trained and untrained tasks separately. Specifically, the untrained task evidences greater activation distribution dimensionality than the trained task. However, the direct comparison between the two tasks did not yield a significant result. The nature of the indication for greater dimensionality in the untrained task is explored and found to be non-linear variation in the data. [ABSTRACT FROM AUTHOR]

The human motor system rapidly adapts to systematic perturbations but the adapted behavior seems to be forgotten equally rapidly. The reason for this forgetting is unclear, as is how to overcome it to promote long-term learning. Here we show that adapted behavior can be stabilized by a period of binary feedback about success and failure in the absence of vector error feedback. We examined die time course of decay after adaptation to a visuomotor rotation through a visual error-clamp condition--trials in which subjects received false visual feedback showing perfect directional performance, regardless of the movements they actually made. Exposure to this error-clamp following initial visuomotor adaptation led to a rapid reversion to baseline behavior. In contrast, exposure to binary feedback after initial adaptation turned the adapted state into a new baseline, to which subjects reverted after transient exposure to another visuomotor rotation. When both binary feedback and vector error were present, some subjects exhibited rapid decay to the original baseline, while others persisted in the new baseline. We propose that learning can be decomposed into two components--a fast-learning, fast-forgetting adaptation process that is sensitive to vector errors and insensitive to task success, and a second process driven by success that learns more slowly but is less susceptible to forgetting. These two learning systems may be recruited to different degrees across individuals. Understanding this competitive balance and exploiting the long-term retention properties of learning through reinforcement is likely to be essential for successful neuro-rehabilitation. [ABSTRACT FROM AUTHOR]

The human primary motor cortex (M1) is robustly activated during visually guided hand movements. M1 multivoxel patterns of functional MRI activation are more correlated during repeated hand movements to the same targets than to greatly differing ones, and therefore potentially contain information about movement direction. It is unclear, however, whether direction specificity is due to the motor command, as implicitly assumed, or to the visual aspects of the task, such as the target location and the direction of the cursor's trajectory. To disambiguate the visual and motor components, different visual-to-motor transformations were applied during an fMRI scan, in which participants made visually guided hand movements in various directions. The first run was the "baseline" (i.e., visual and motor mappings were matched); in the second run ("rotation"), the cursor movement was rotated by 45° with respect to the joystick movement. As expected, positive correlations were seen between the M1 multivoxel patterns evoked by the baseline run and by the rotation run, when the two movements were matched in their movement direction but the visual aspects differed. Importantly, similar correlations were observed when the visual elements were matched but the direction of hand movement differed. This indicates that M1 is sensitive to both motor and visual components of the task. However, repeated observation of the cursor movement without concurrent joystick control did not elicit significant activation in M1 or any correlated patterns of activation. Thus, visual aspects of movement are encoded in M1 only when they are coupled with motor consequences. [ABSTRACT FROM AUTHOR]