Multiple roles of motor imagery during action observation

Over the last 20 years, the topics of action observation (AO) and motor imagery (MI) have been largely studied in isolation from each other, despite the early integrative account by Jeannerod (1994, 2001). Recent neuroimaging studies demonstrate enhanced cortical activity when AO and MI are performed concurrently (“AO+MI”), compared to either AO or MI performed in isolation. These results indicate the potentially beneficial effects of AO+MI, and they also demonstrate that the underlying neurocognitive processes are partly shared. We separately review the evidence for MI and AO as forms of motor simulation, and present two quantitative literature analyses that indeed indicate rather little overlap between the two bodies of research. We then propose a spectrum of concurrent AO+MI states, from congruent AO+MI where the contents of AO and MI widely overlap, over coordinative AO+MI, where observed and imagined action are different but can be coordinated with each other, to cases of conflicting AO+MI. We believe that an integrative account of AO and MI is theoretically attractive, that it should generate novel experimental approaches, and that it can also stimulate a wide range of applications in sport, occupational therapy, and neurorehabilitation

The cerebellum and motor dysfunction in neuropsychiatric disorders

The cerebellum is densely interconnected with sensory-motor areas of the cerebral cortex, and in man, the great expansion of the association areas of cerebral cortex is also paralleled by an expansion of the lateral cerebellar hemispheres. It is therefore likely that these circuits contribute to non-motor cognitive functions, but this is still a controversial issue. One approach is to examine evidence from neuropsychiatric disorders of cerebellar involvement. In this review, we narrow this search to test whether there is evidence of motor dysfunction associated with neuropsychiatric disorders consistent with disruption of cerebellar motor function. While we do find such evidence, especially in autism, schizophrenia and dyslexia, we caution that the restricted set of motor symptoms does not suggest global cerebellar dysfunction. Moreover, these symptoms may also reflect involvement of other, extra-cerebellar circuits and detailed examination of specific sub groups of individuals within each disorder may help to relate such motor symptoms to cerebellar morphology

The effect of the interval-between-sessions on prefrontal transcranial direct current stimulation (tDCS) on cognitive outcomes: a systematic review and meta-analysis

Recently, there has been wide interest in the effects of transcranial direct current stimulation (tDCS) of the dorsolateral prefrontal cortex (DLPFC) on cognitive functioning. However, many methodological questions remain unanswered. One of them is whether the time interval between active and sham-controlled stimulation sessions, i.e. the interval between sessions (IBS), influences DLPFC tDCS effects on cognitive functioning. Therefore, a systematic review and meta-analysis was performed of experimental studies published in PubMed, Science Direct, and other databases from the first data available to February 2016. Single session sham-controlled within-subject studies reporting the effects of tDCS of the DLPFC on cognitive functioning in healthy controls and neuropsychiatric patients were included. Cognitive tasks were categorized in tasks assessing memory, attention, and executive functioning. Evaluation of 188 trials showed that anodal vs. sham tDCS significantly decreased response times and increased accuracy, and specifically for the executive functioning tasks, in a sample of healthy participants and neuropsychiatric patients (although a slightly different pattern of improvement was found in analyses for both samples separately). The effects of cathodal vs. sham tDCS (45 trials), on the other hand, were not significant. IBS ranged from less than 1 h to up to 1 week (i.e. cathodal tDCS) or 2 weeks (i.e. anodal tDCS). This IBS length had no influence on the estimated effect size when performing a meta-regression of IBS on reaction time and accuracy outcomes in all three cognitive categories, both for anodal and cathodal stimulation. Practical recommendations and limitations of the study are further discussed

Computational neurorehabilitation: modeling plasticity and learning to predict recovery

Despite progress in using computational approaches to inform medicine and neuroscience in the last 30 years, there have been few attempts to model the mechanisms underlying sensorimotor rehabilitation. We argue that a fundamental understanding of neurologic recovery, and as a result accurate predictions at the individual level, will be facilitated by developing computational models of the salient neural processes, including plasticity and learning systems of the brain, and integrating them into a context specific to rehabilitation. Here, we therefore discuss Computational Neurorehabilitation, a newly emerging field aimed at modeling plasticity and motor learning to understand and improve movement recovery of individuals with neurologic impairment. We first explain how the emergence of robotics and wearable sensors for rehabilitation is providing data that make development and testing of such models increasingly feasible. We then review key aspects of plasticity and motor learning that such models will incorporate. We proceed by discussing how computational neurorehabilitation models relate to the current benchmark in rehabilitation modeling – regression-based, prognostic modeling. We then critically discuss the first computational neurorehabilitation models, which have primarily focused on modeling rehabilitation of the upper extremity after stroke, and show how even simple models have produced novel ideas for future investigation. Finally, we conclude with key directions for future research, anticipating that soon we will see the emergence of mechanistic models of motor recovery that are informed by clinical imaging results and driven by the actual movement content of rehabilitation therapy as well as wearable sensor-based records of daily activity

The therapeutic potential of exercise to improve mood, cognition, and sleep in Parkinson's disease

Published in final edited form as: Mov Disord. 2016 January ; 31(1): 23–38. doi:10.1002/mds.26484.In addition to the classic motor symptoms, Parkinson's disease (PD) is associated with a variety of nonmotor symptoms that significantly reduce quality of life, even in the early stages of the disease. There is an urgent need to develop evidence‐based treatments for these symptoms, which include mood disturbances, cognitive dysfunction, and sleep disruption. We focus here on exercise interventions, which have been used to improve mood, cognition, and sleep in healthy older adults and clinical populations, but to date have primarily targeted motor symptoms in PD. We synthesize the existing literature on the benefits of aerobic exercise and strength training on mood, sleep, and cognition as demonstrated in healthy older adults and adults with PD, and suggest that these types of exercise offer a feasible and promising adjunct treatment for mood, cognition, and sleep difficulties in PD. Across stages of the disease, exercise interventions represent a treatment strategy with the unique ability to improve a range of nonmotor symptoms while also alleviating the classic motor symptoms of the disease. Future research in PD should include nonmotor outcomes in exercise trials with the goal of developing evidence‐based exercise interventions as a safe, broad‐spectrum treatment approach to improve mood, cognition, and sleep for individuals with PD.This work was supported by the National Institute of Mental Health (F31MH102961 to G.O.R.)

Articulating: the neural mechanisms of speech production

Speech production is a highly complex sensorimotor task involving tightly coordinated processing across large expanses of the cerebral cortex. Historically, the study of the neural underpinnings of speech suffered from the lack of an animal model. The development of non-invasive structural and functional neuroimaging techniques in the late 20th century has dramatically improved our understanding of the speech network. Techniques for measuring regional cerebral blood flow have illuminated the neural regions involved in various aspects of speech, including feedforward and feedback control mechanisms. In parallel, we have designed, experimentally tested, and refined a neural network model detailing the neural computations performed by specific neuroanatomical regions during speech. Computer simulations of the model account for a wide range of experimental findings, including data on articulatory kinematics and brain activity during normal and perturbed speech. Furthermore, the model is being used to investigate a wide range of communication disorders.R01 DC002852 - NIDCD NIH HHS; R01 DC007683 - NIDCD NIH HHS; R01 DC016270 - NIDCD NIH HHSAccepted manuscrip

The Effect of Physical Activity on Children's Logical-Mathematical Intelligence

Research between physical activity and cognitive work in children is still relatively rare and inconsistent, even though children's motor development and cognitive learning are related to positive effects on academic work. This study aims to determine the increase in mathematical logical intelligence of early childhood through physical activity. This is action research. This type of research was a sequential exploratory design. Data analysis in this study used a combined quantitative and qualitative analysis (Mix Method). The results showed increasing logical mathematics intelligence in DKI Jakarta's childhood. The initial assessment results showed that the average value of the child's logical mathematics intelligence was 28 and then increased to 57 in the final assessment of cycle 1 and continued to increase to 78 in the final assessment of cycle 2. Physical activity learning with games strategies increasing the logical mathematics intelligence in childhood in Jakarta Kindergarten. 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