Cognitive and Motor Rehabilitation and Development
Parkinson’s disease has serious impacts on motor and cognitive function, leading to balance instability, isolation and reduced independence and quality of life. This work shows evidence for positive and translatable effects on multiple dimensions of Parkinson’s disease symptom profiles with group exercise and dance training and on specific cognitive symptoms with daily computer-based training. Networks affected by Parkinson’s disease are also implicated in predictive and continuous control of body movement, and rhythm and timing. Rhythmic auditory stimulation is the most clinically effective application of music cognition research to date and has the potential to improve performance and quality of life of many individuals while also contributing to basic research on brain network architecture and dynamics and on neurodegenerative disease. In addition, I extended change point analysis methods, which I learned in Parkinson’s disease rehabilitation and training research, to infant data in order to analyze the developmental trajectory of rhythmic limb and vocal behavior in a typically developing infant.
 Nguyen, H.M., Aravindakshan, A., Ross, J.M., & Disbrow, E.A. (2020). Time course of cognitive training in Parkinson disease. NeuroRehabilitation, 46, 311-320.
 Ventura, M.I., Barnes, D.E., Ross, J.M., Lanni, K.E., Sigvardt, K.A., & Disbrow, E.A (2016). A pilot study to evaluate multi-dimensional effects of dance for people with Parkinson’s disease. Contemp. Clin. Trials, 51, 50-55.
 Lanni, K.E., Ross, J.M., Higginson, C.I., Dressler, E.M., Sigvardt, K.A., Zhang, L., Malhado-Chang, N., & Disbrow, E.A. (2014). Perceived and performance-based executive dysfunction in Parkinson’s disease. Journal of Clinical and Experimental Neuropsychology, 36:4.
 Abney, D.H., Warlaumont, A.S., Haussman, A., Ross, J.M., & Wallot, S. (2014). Using non-linear methods to quantify changes in infant limb movements and vocalizations. Front. Psychol., 5:771.
Figure 1. The pairing of dynamical systems theory and complexity science brings novel concepts and methods to the study of infant motor development.
This longitudinal case study presents a new approach to characterizing the dynamics of infant limb and vocalization behaviors. A single infant’s vocalizations and limb movements were recorded from 51-days to 305-days of age. On each recording day, accelerometers were placed on all four of the infant’s limbs and an audio recorder was worn on the child’s chest. Using nonlinear time series analysis methods, such as recurrence quantification analysis and Allan factor, we quantified changes in the stability and multiscale properties of the infant’s behaviors across age as well as how these dynamics relate across modalities and effectors. We observed that particular changes in these dynamics preceded or coincided with the onset of various developmental milestones. For example, the largest changes in vocalization dynamics preceded the onset of canonical babbling. The results show that nonlinear analyses can help to understand the functional co-development of different aspects of infant behavior. (A) An overview of dynamic measures of development as a function of age, modality, and effector. Change point convergence between Taylor’s method (cumulative sum, CUSUM) and Mean Square Error (MSE) are indicated by dashed vertical lines. (B) Change point results with language and other motor milestones. Horizontal bars correspond with particular change points. Age is shown as a function of recording session. Figure adapted from Abney et al., 2014.
Figure 2. Computer-based cognitive training can improve internally generated (un-cued) movement initiation in people with Parkinson’s disease (PD).
Further, we show that optimal training duration can be relatively short (~8 days) and that more impaired patients receive the most gain, indicating that cognitive training should be tailored to individual needs. To determine the optimal training duration for computer-based neurorehabilitation of internally generated movement initiation, we studied 19 patients with PD and 21 age-matched controls, ages 50-85 years. The study included pre- and post-training evaluations and 30 training sessions. Computer training consisted of cued and un-cued movement trials. The training was adaptive in difficulty and designed to train internally generated (un-cued) movements. Outcome measures were reaction time and error rate, and cumulative sum (CUSUM) change point analysis was used to identify peak day of training improvement. Participants with PD were divided into impaired (IPD) and unimpaired (UPD) groups based on mean control group pre-training performance. All 3 groups showed improved reaction times and error rates for IR trials. However, the IPD group demonstrated significantly greater improvement in reaction times. Training was most effective in participants with greater disease severity and duration. Peak day of training improvement for the IPD group was 8 days. The figure shows the cumulative sum chart of the 4-digit bimanual internally generated response trials. Error bars represent standard error. Maximum points in the curve indicate the peak days of training. For patients in the IPD, UPD, and control groups, the peak days of training were 8, 9, and 10, respectively. Figure from Nguyen et al., 2020.