Trade-off between frequency and precision during stepping movements: Kinematic and BOLD brain activation patterns

Abstract

The central nervous system has the ability to adapt our locomotor pattern to produce a wide range of gait modalities and velocities. In reacting to external pacing stimuli, deviations from an individual preferred cadence provoke a concurrent decrease in accuracy that suggests the existence of a trade-off between frequency and precision; a compromise that could result from the specialization within the control centers of locomotion to ensure a stable transition and optimal adaptation to changing environment. Here, we explore the neural correlates of such adaptive mechanisms by visually guiding a group of healthy subjects to follow three comfortable stepping frequencies while simultaneously recording their BOLD responses and lower limb kinematics with the use of a custom-built treadmill device. In following the visual stimuli, subjects adopt a common pattern of symmetric and anti-phase movements across pace conditions. However, when increasing the stimulus frequency, an improvement in motor performance (precision and stability) was found, which suggests a change in the control mode from reactive to predictive schemes. Brain activity patterns showed similar BOLD responses across pace conditions though significant differences were observed in parietal and cerebellar regions. Neural correlates of stepping precision were found in the insula, cerebellum, dorsolateral pons and inferior olivary nucleus, whereas neural correlates of stepping stability were found in a distributed network, suggesting a transition in the control strategy across the stimulated range of frequencies: from unstable/reactive at lower paces (i.e., stepping stability managed by subcortical regions) to stable/predictive at higher paces (i.e., stability managed by cortical regions). Hum Brain Mapp 37:1722-1737, 2016. © 2016 Wiley Periodicals, Inc.

Keywords: effect of frequency; functional neuroimaging; kinematics; locomotion; lower limb movements; precision; predictive strategy; reactive strategy.

Figure 1

A. Experimental setup of the pseudo‐gait MRI compatible device. B. The visual stimulus employed during the paradigm consisted in two footprints moving constantly and vertically at 0.8, 1,2, and 1.75 Hz depending on the condition. C. Alternation of motor and resting blocks during the sequence presentation showing the onsets and durations of the condition blocks. © [2014] IEEE. Figure 1A,B Reprinted, with permission, from Martínez et al., 2014. [Color figure can be viewed in the online issue, which is available at http://wileyonlinelibrary.com.]

Figure 2

Effect of frequency in the kinematic parameters employed for characterizing the lower limb movement patterns: (A) SF: stepping frequency, (B) SA: stepping amplitude, (C) AC: asymmetry coefficient, (D) RP: relative phase, (E) DS: deviation score, and (F) CV: coefficient of variability. Statistically significant differences (P < 0.05) on features between conditions are indicated. [Color figure can be viewed in the online issue, which is available at http://wileyonlinelibrary.com.]

Figure 3

Patterns of brain activation (hot color scale)/deactivation (cold color scale) corresponding to the (A) C_0.8, (B) C_1.2, and (C) C_1.75 vs. rest contrasts, P < 0.001, FWE‐ corrected at the cluster level. Qualitatively, similar bilateral activation and deactivation maps were detected for the three frequencies. At the cortical level, significant bilateral overlapping activations were found in the inferior frontal cortex (including anterior insula), premotor cortex, supplementary motor area (SMA), primary sensorimotor cortex (SM1), cingulate motor cortex (CMC), superior parietal cortex (SPC), supramarginal and angular gyri, and inferior parietal cortex (IPC). Subcortically, significant activations covered the cerebellar regions within the anterior vermis (lobes I–IV). Deactivation covered bilaterally areas in the superior frontal and medial orbital lobes, postcentral and angular gyri, anterior, middle and posterior cingulate cortices, cuneus, precuneus, lingual and fusiform gyri, middle and inferior temporal lobes, parahippocampal gyrus, hippocampus, and left middle frontal gyrus. At the subcortical level, decreases of activation were found in the bilateral caudate nucleus, thalamus, cerebellum lobule VI, Crus 1 and Crus 2, lobule IX, central pons and medulla oblongata.

Figure 4

Brain areas showing an effect of the stepping frequency. A. T1 axial sections displaying clusters were BOLD activations showed a significant effect of frequency (P < 0.001, corrected for multiple comparisons). B. Percent signal Change (PSC) in the (1) L cerebellum VIIIa (3,‐79,‐42), (2) L Cerebellum VI (−15, −82,‐17), and (3) L precuneus (−2, −58, 34). NOTE: ROIs were selected from the ANOVA using a 6 mm‐sphere VOI centered in the cluster maxima. R: Right, L: Left.

Figure 5

Neural correlates of visuomotor precision during stepping movements (multiple regression analysis with the DS parameter, P < 0.001, k > 10). Responses were found in the R insula, R Vermis, L DL pons and R inferior olive. DL: Dorsolateral. R: Right, L: Left.

Figure 6

Neural correlates of pace stability during visually‐guided stepping movements (multiple regression analysis with the CV parameter, P < 0.001, k > 10). The localization of the BOLD responses linearly correlating with the CV are colored in hot T‐scale whereas BOLD responses with negative correlation with the CV are colored in cold T‐scale.