This qualitative study explored the experience of participating in a research study using magnetic resonance imaging (MRI) for children with autism spectrum disorder (ASD), typically developing (TYP) children, and their parent. It also assessed the feasibility, efficacy, and acceptability of the Going to MRI for a Research Study© iPad application (app), developed by the primary author, available for use for MRI preparation. The app provides a description of the steps of the MRI procedure, from the child’s perspective, outlining expected behaviors and responses. Ten English-speaking parent/child dyads (n = 20) participated in an audiotaped question guide-facilitated telephone interview about their experience in the MRI study. Participants confirmed the iPad app's feasibility, efficacy, and acceptability. ASD child/parent themes differed from TYP child/parent themes. More children with ASD who used the app completed the MRI than without it. The iPad app may help children with ASD complete MRIs in future studies.

INTRODUCTION:Current research suggests that the neuropathology of dementia-including brain changes leading to memory impairment and cognitive decline-is evident years before the onset of this disease. Older adults with cognitive decline have reduced functional independence and quality of life, and are at greater risk for developing dementia. Therefore, identifying biomarkers that can be easily assessed within the clinical setting and predict cognitive decline is important. Early recognition of cognitive decline could promote timely implementation of preventive strategies.METHODS:We included 89 community-dwelling adults aged 70 years and older in our study, and collected 32 measures of physical function, health status and cognitive function at baseline. We utilized an L1-L2 regularized regression model (elastic net) to identify which of the 32 baseline measures were strongly predictive of cognitive function after one year. We built three linear regression models: 1) based on baseline cognitive function, 2) based on variables consistently selected in every cross-validation loop, and 3) a full model based on all the 32 variables. Each of these models was carefully tested with nested cross-validation.RESULTS:Our model with the six variables consistently selected in every cross-validation loop had a mean squared prediction error of 7.47. This number was smaller than that of the full model (115.33) and the model with baseline cognitive function (7.98). Our model explained 47% of the variance in cognitive function after one year.DISCUSSION:We built a parsimonious model based on a selected set of six physical function and health status measures strongly predictive of cognitive function after one year. In addition to reducing the complexity of the model without changing the model significantly, our model with the top variables improved the mean prediction error and R-squared. These six physical function and health status measures can be easily implemented in a clinical setting.

Our long-term goal is to understand the extent to which motor impairments reported in autism may be related to abnormalities of brain function. We previously described a robotic joystick and video game system that allows us to record functional magnetic resonance images (FMRI) while adult humans make goal-directed wrist motions. We anticipated several challenges in extending this approach to studying goal-directed behaviors in children with autism spectrum disorders (ASD) and in typically developing (TYP) children. In particular we were concerned that children with autism may express increased levels of anxiety as compared to typically developing children due to the loud sounds and small enclosed space of the MRI scanner. We also were concerned that both groups of children might become restless during testing, leading to an unacceptable amount of head movement. Here we evaluated both the extent to which autistic and typically developing children exhibit anxiety during our experimental protocol and their ability to comply with task instructions. Our experimental controls were successful in minimizing group differences in drop-out due to anxiety. Kinematic performance and head motion also were similar across groups. Both groups of children engaged cortical regions (frontal, parietal, temporal, occipital). In addition, the ASD group exhibited task-related correlations in subcortical regions (cerebellum, thalamus), whereas correlations in the TYP group did not reach statistical significance in subcortical regions. Four distinct regions in frontal cortex showed a significant group difference such that TYP children exhibited positive correlations between the hemodynamic response and movement onset, whereas children with ASD exhibited negative correlations. These findings demonstrate feasibility of simultaneous application of robotic manipulation and functional imaging to study goal-directed motor behaviors in autistic and typically developing children.

Electroencephalogram coherence was measured in children with autism spectrum disorders ( ASD ) and control children at baseline and while watching videos of a familiar and unfamiliar person reading a story. Coherence was measured between the left and right hemispheres of the frontal, parietal, and temporal‐parietal lobes (interhemispheric) and between the frontal and parietal lobes in each hemisphere (intrahemispheric). A data‐reduction technique was employed to identify the frequency (alpha) that yielded significant differences in video conditions. Children with ASD displayed reduced coherence at the alpha frequency between the left and right temporal‐parietal lobes in all conditions and reduced coherence at the alpha frequency between left and right frontal lobes during baseline. No group differences in intrahemispheric coherence at the alpha frequency emerged at the chosen statistical threshold. Results suggest decreased interhemispheric connectivity in frontal and temporal‐parietal regions in children with ASD compared to controls. Autism Res 2014, 7: 334–343. © 2014 International Society for Autism Research, Wiley Periodicals, Inc.

An unanswered question concerning the neural basis of autism spectrum disorders (ASD) is how sensorimotor deficits in individuals with ASD are related to abnormalities of brain function. We previously described a robotic joystick and video game system that allows us to record functional magnetic resonance images (FMRI) while adult humans make goaldirected wrist motions. We anticipated several challenges in extending this approach to studying goal-directed behaviors in children with ASD and in typically developing (TYP) children. In particular we were concerned that children with autism may express increased levels of anxiety as compared to typically developing children due to the loud sounds and small enclosed space of the MRI scanner. We also were concerned that both groups of children might become restless during testing, leading to an unacceptable amount of head movement. Here we performed a pilot study evaluating the extent to which autistic and typically developing children exhibit anxiety during our experimental protocol as well as their ability to comply with task instructions. Our experimental controls were successful in minimizing group differences in drop-out due to anxiety. Kinematic performance and head motion also were similar across groups. Both groups of children engaged cortical regions (frontal, parietal, temporal, occipital) while making goaldirected movements. In addition, the ASD group exhibited taskrelated correlations in subcortical regions (cerebellum, thalamus), whereas correlations in the TYP group did not reach statistical significance in subcortical regions. Four distinct regions in frontal cortex showed a significant group difference such that TYP children exhibited positive correlations between the hemodynamic response and movement, whereas children with ASD exhibited negative correlations. These findings demonstrate feasibility of simultaneous application of robotic manipulation and functional imaging to study goal-directed motor behaviors in autistic and typically developing children. The findings also suggest the presence of marked changes in neural activation during a sensorimotor task requiring goaldirected movement.

An unanswered question concerning the neural basis of autism spectrum disorders (ASD) is how sensorimotor deficits in individuals with ASD are related to abnormalities of brain function. We previously described a robotic joystick and video game system that allows us to record functional magnetic resonance images (FMRI) while adult humans make goal-directed wrist motions. We anticipated several challenges in extending this approach to studying goal-directed behaviors in children with ASD and in typically developing (TYP) children. In particular we were concerned that children with autism may express increased levels of anxiety as compared to typically developing children due to the loud sounds and small enclosed space of the MRI scanner. We also were concerned that both groups of children might become restless during testing, leading to an unacceptable amount of head movement. Here we performed a pilot study evaluating the extent to which autistic and typically developing children exhibit anxiety during our experimental protocol as well as their ability to comply with task instructions. Our experimental controls were successful in minimizing group differences in drop-out due to anxiety. Kinematic performance and head motion also were similar across groups. Both groups of children engaged cortical regions (frontal, parietal, temporal, occipital) while making goal-directed movements. In addition, the ASD group exhibited task-related correlations in subcortical regions (cerebellum, thalamus), whereas correlations in the TYP group did not reach statistical significance in subcortical regions. Four distinct regions in frontal cortex showed a significant group difference such that TYP children exhibited positive correlations between the hemodynamic response and movement, whereas children with ASD exhibited negative correlations. These findings demonstrate feasibility of simultaneous application of robotic manipulation and functional imaging to study goal-directed motor behaviors in autistic and typically developing children. The findings also suggest the presence of marked changes in neural activation during a sensorimotor task requiring goal-directed movement.

Cognitive impairment is a significant and global health care concern. Older adults with cognitive impairment have reduced functional independence and reduced quality of life. Given the population is aging at a rapid rate, early detection of risk for cognitive decline would promote timely implementation of prevention strategies. To facilitate uptake and use, screening tools must be feasible to use in clinical settings. Emerging evidence indicates a strong association between physical performance and cognitive function in older adults. Thus, we aimed to identify clinical measures of mobility and health status that are significant predictors of cognitive function, assessed by the Montreal Cognitive Assessment (MoCA), over a 12-month period. We used data acquired from 91 older women (aged 65 to 75 years) who participated in a 12-month randomized controlled trial of exercise. Thirty three measures were collected at baseline: 1) age, 2) MoCA, 3) number of prescribed medications, 4) number of supplements taken, 5) 29 mobility and health status scores. A L1-L2 regularized regression model (AKA Elastic Net) with jack-knife was constructed to predict MoCA score after 12 months. The top 10 significant predictors of MoCA score at 12 months were: age, baseline MoCA score, number of supplements taken, experimental group, and six mobility and health status scores of: 1) the Short Physical Performance Battery (SPPB) balance score (out of 4), 2) total Activities-Specific Balance Confidence (ABC) score, 3) SPPB walking score (out of 4), 4) visual contrast score, 5) waist-hip ratio, and 6) Physiological Profile Assessment (PPA). Collectively, these top 10 predictors could explain 42% of the variance in MoCA score at 12 months, which was statistically larger than the variance accounted for by any of the 34 individual predictors (p < 0.001).

Thirteen autistic and 14 typically developing children (controls) imitated hand/arm gestures and performed mirror drawing; both tasks assessed ability to reorganize the relationship between spatial goals and the motor commands needed to acquire them. During imitation, children with autism were less accurate than controls in replicating hand shape, hand orientation, and number of constituent limb movements. During shape tracing, children with autism performed accurately with direct visual feedback, but when viewing their hand in a mirror, some children with autism generated fewer errors than controls whereas others performed much worse. Large mirror drawing errors correlated with hand orientation and hand shape errors in imitation, suggesting that visuospatial information processing deficits may contribute importantly to functional motor coordination deficits in autism.

We used functional MR imaging (FMRI), a robotic manipulandum and systems identification techniques to examine neural correlates of predictive compensation for spring-like loads during goal-directed wrist movements in neurologically-intact humans. Although load changed unpredictably from one trial to the next, subjects nevertheless used sensorimotor memories from recent movements to predict and compensate upcoming loads. Prediction enabled subjects to adapt performance so that the task was accomplished with minimum effort. Population analyses of functional images revealed a distributed, bilateral network of cortical and subcortical activity supporting predictive load compensation during visual target capture. Cortical regions--including prefrontal, parietal and hippocampal cortices--exhibited trial-by-trial fluctuations in BOLD signal consistent with the storage and recall of sensorimotor memories or "states" important for spatial working memory. Bilateral activations in associative regions of the striatum demonstrated temporal correlation with the magnitude of kinematic performance error (a signal that could drive reward-optimizing reinforcement learning and the prospective scaling of previously learned motor programs). BOLD signal correlations with load prediction were observed in the cerebellar cortex and red nuclei (consistent with the idea that these structures generate adaptive fusimotor signals facilitating cancelation of expected proprioceptive feedback, as required for conditional feedback adjustments to ongoing motor commands and feedback error learning). Analysis of single subject images revealed that predictive activity was at least as likely to be observed in more than one of these neural systems as in just one. We conclude therefore that motor adaptation is mediated by predictive compensations supported by multiple, distributed, cortical and subcortical structures.