Impact of visual rotations on heading direction and center of mass control during steady-state gait.

Visual information is essential to navigate the environment and maintain postural stability during gait. Visual field rotations alter the perceived heading direction, resulting in gait trajectory deviations, known as visual coupling. It is unclear how center of mass (CoM) control relative to a continuously changing base of support (BoS) is adapted to facilitate visual coupling. This study aimed to characterize mediolateral (ML) balance control during visual coupling in steady-state gait. Sixteen healthy participants walked on an instrumented treadmill, naive to sinusoidal low-frequency (0.1 Hz) rotations of the virtual environment around the vertical axis. Rotations were continuous with 1) high or 2) low amplitude or were 3) periodic with 10-s intervals. Visual coupling was characterized with cross-correlations between CoM trajectory and visual rotations. Balance control was characterized with the ML margin of stability (MoSML) and by quantifying foot placement control as the relation between CoM dynamics and lateral foot placement. Visual coupling was strong on a group level (continuous low: 0.88, continuous high: 0.91, periodic: 0.95) and moderate to strong on an individual level. Higher rotation amplitudes induced stronger gait trajectory deviations. The MoSML decreased toward the deviation direction and increased at the opposite side. Foot placement control was similar compared with regular gait. Furthermore, pelvis and foot reorientation toward the rotation direction was observed. We concluded that visual coupling was facilitated by reorientating the body and shifting the extrapolated CoMML closer to the lateral BoS boundary toward the adjusted heading direction while preserving CoM excursion and foot placement control.NEW & NOTEWORTHY Healthy, naive participants were unaware of subtle, low-frequency rotations of the visual field but still coupled their gait trajectory to a rotating virtual environment. In response, participants decreased their margin of stability toward the new heading direction, without changing the center of mass excursion magnitude and foot placement strategy.

Characterization of EEG-based functional brain networks in myotonic dystrophy type 1.

OBJECTIVE: In the autosomal dominant, multisystem, chronic progressive disease myotonic dystrophy type 1 (DM1), cognitive deficits may originate from disrupted functional brain networks. We aimed to use network analysis of resting-state electro-encephalography (EEG) recordings of patients with DM1 and matched unaffected controls to investigate changes in network organization in large-scale functional brain networks and correlations with cognitive deficits. METHODS: In this cross-sectional study, 28 adult patients with genetically confirmed DM1 and 26 age-, sex- and education-matched unaffected controls underwent resting-state EEG and neuropsychological assessment. We calculated the Phase Lag Index (PLI) to determine EEG frequency-dependent functional connectivity between brain regions. Functional brain networks were characterized by applying concepts from graph theory and compared between-groups. Network topology was evaluated using the minimum spanning tree (MST). We evaluated correlations between network metrics and neuropsychological tests that showed statistically significant between-group differences. RESULTS: Functional connectivity estimated as whole-brain median PLI for DM1 patients versus healthy controls was higher in theta band (0.141 [0.050] versus 0.125 [0.018], p = 0.029), and lower in the upper alpha band (0.154 [0.048] versus 0.182 [0.073], p = 0.038), respectively. Functional MST-constructed networks in DM1 patients were significantly dissimilar from healthy controls in the delta, (p = 0.009); theta, (p = 0.009); lower alpha, (p = 0.036); and upper alpha, (p = 0.008) bands. In evaluation of local MST network measures, trends toward networks with higher global integration in the theta band and lower global integration in the upper alpha band were observed. Compared to unaffected controls, DM1 patients performed worse on tests of attention, motor function, executive function and visuospatial memory. Visuospatial memory correlated with the global median PLI in the upper alpha band; the Stroop interference test correlated with betweenness centrality in this band. CONCLUSION: This study supports the hypothesis that brain changes in DM1 give rise to disrupted functional network organization, as modelled with EEG-based networks. Further study may help unravel the relations with clinical brain-related DM1 symptoms. SIGNIFICANCE: EEG network analysis has potential to help understand brain related DM1 phenotypes. FUNDING: This work was supported by the European Community's Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 305697 (OPTIMISTIC) and the Marigold Foundation.