Kinesthesis
Research Papers
Neurofeedback-guided kinesthetic motor imagery training in Parkinson's disease: Randomized trial
BACKGROUND: Parkinson's disease (PD) causes difficulty with maintaining the speed, size, and vigor of movements, especially when they are internally generated. We previously proposed that the insula is important in motivating intentional movement via its connections with the dorsomedial frontal cortex (dmFC). We demonstrated that subjects with PD can increase the right insula-dmFC functional connectivity using fMRI-based neurofeedback (NF) combined with kinesthetic motor imagery (MI). The current study is a randomized clinical trial testing whether NF-guided kinesthetic MI training can improve motor performance and increase task-based and resting-state right insula-dmFC functional connectivity in subjects with PD. METHODS: We assigned nondemented subjects with mild PD (Hoehn & Yahr stage ≤ 3) to the experimental kinesthetic MI with NF (MI-NF, n = 22) and active control visual imagery (VI, n = 22) groups. Only the MI-NF group received NF-guided MI training (10-12 runs). The NF signal was based on the right insula-dmFC functional connectivity strength. All subjects also practiced their respective imagery tasks at home daily for 4 weeks. Post-training changes in 1) task-based and resting-state right insula-dmFC functional connectivity were the primary imaging outcomes, and 2) MDS-UPDRS motor exam and motor function scores were the primary and secondary clinical outcomes, respectively. RESULTS: The MI-NF group was not significantly different from the VI group in any of the primary imaging or clinical outcome measures. The MI-NF group reported subjective improvement in kinesthetic body awareness. There was significant and comparable improvement only in motor function scores in both groups (secondary clinical outcome). This improvement correlated with NF regulation of the right insula-dmFC functional connectivity only in the MI-NF group. Both groups showed specific training effects in whole-brain functional connectivity with distinct neural circuits supporting kinesthetic motor and visual imagery (exploratory imaging outcome). CONCLUSIONS: The functional connectivity-based NF regulation was unsuccessful, however, both kinesthetic MI and VI practice improved motor function in our cohort with mild PD.
View Full Paper →The BOLD response in primary motor cortex and supplementary motor area during kinesthetic motor imagery based graded fMRI neurofeedback
There is increasing interest in exploring the use of functional MRI neurofeedback (fMRI-NF) as a therapeutic technique for a range of neurological conditions such as stroke and Parkinson's disease (PD). One main therapeutic potential of fMRI-NF is to enhance volitional control of damaged or dysfunctional neural nodes and networks via a closed-loop feedback model using mental imagery as the catalyst of self-regulation. The choice of target node/network and direction of regulation (increase or decrease activity) are central design considerations in fMRI-NF studies. Whilst it remains unclear whether the primary motor cortex (M1) can be activated during motor imagery, the supplementary motor area (SMA) has been robustly activated during motor imagery. Such differences in the regulation potential between primary and supplementary motor cortex are important because these areas can be differentially affected by a stroke or PD, and the choice of fMRI-NF target and grade of self-regulation of activity likely have substantial influence on the clinical effects and cost effectiveness of NF-based interventions. In this study we therefore investigated firstly whether healthy subjects would be able to achieve self-regulation of the hand-representation areas of M1 and the SMA using fMRI-NF training. There was a significant decrease in M1 neural activity during fMRI-NF, whereas SMA neural activity was increased, albeit not with the predicated graded effect. This study has important implications for fMRI-NF protocols that employ motor imagery to modulate activity in specific target regions of the brain and to determine how they may be tailored for neurorehabilitation.
View Full Paper →Optimal spatial frequencies for discrimination of motion direction in optic flow patterns
Spatial frequency tuning functions were measured for direction discrimination of optic flow patterns. Three subjects discriminated the direction of a curved motion path using computer generated optic flow patterns composed of randomly positioned dots. Performance was measured with unfiltered patterns and with patterns that were spatially filtered across a range of spatial frequencies (center spatial frequencies of 0.4, 0.8, 1.6, 3.2, 6.4, and 9.6 c/deg). The same subjects discriminated the direction of uniform, translational motion on the fronto-parallel plane. The uniform motion patterns were also composed of randomly positioned dots, that were either unfiltered or filtered with the same spatial filters used for the optic flow patterns. The peak spatial frequency was the same for both the optic flow and uniform motion patterns. For both types of motion, a narrow band (1.5 octaves) of optimal spatial frequencies was sufficient to support the same level of performance as found with unfiltered, broadband patterns. Additional experiments demonstrated that the peak spatial frequency for the optic flow patterns varies with mean image speed in the same manner as has been reported for moving sinusoidal gratings. These findings confirm the hypothesis that the outputs of the local motion mechanisms thought to underlie the perception of uniform motion provide the inputs to, and constrain the operation of, the mechanism that processes self motion from optic flow patterns.
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