Neural Correlates of Single- and Dual-Task Walking in the Real World

Abstract

Recent developments in mobile brain-body imaging (MoBI) technologies have enabled studies of human locomotion where subjects are able to move freely in more ecologically valid scenarios. In this study, MoBI was employed to describe the behavioral and neurophysiological aspects of three different commonly occurring walking conditions in healthy adults. The experimental conditions were self-paced walking, walking while conversing with a friend and lastly walking while texting with a smartphone. We hypothesized that gait performance would decrease with increased cognitive demands and that condition-specific neural activation would involve condition-specific brain areas. Gait kinematics and high density electroencephalography (EEG) were recorded whilst walking around a university campus. Conditions with dual tasks were accompanied by decreased gait performance. Walking while conversing was associated with an increase of theta (θ) and beta (β) neural power in electrodes located over left-frontal and right parietal regions, whereas walking while texting was associated with a decrease of β neural power in a cluster of electrodes over the frontal-premotor and sensorimotor cortices when compared to walking whilst conversing. In conclusion, the behavioral "signatures" of common real-life activities performed outside the laboratory environment were accompanied by differing frequency-specific neural "biomarkers". The current findings encourage the study of the neural biomarkers of disrupted gait control in neurologically impaired patients.

Keywords: EEG; gait monitoring; mobile brain-body imaging; multitasking; neuroimaging; urban environment.

Figure 1

UEL Stratford Campus map and subjects walking path. Subjects were first prepared in the laboratory (pink star) and then accompanied outside along the black-dashed path. They were then given specific instructions on the path to follow during the experiment (red-dashed path), starting and finishing always in the same position (yellow start).

Figure 2

Mobile Setup for real-world experiments. During walking experiments, subjects carried all the setup on themselves. Brain activity was recorded by a 64-channel electroencephalography (EEG) Waveguard cap connected to the EEGoPro amplifier which was placed into a backpack together with a DELL tablet on which the recording software ran. Contact switches were placed underneath the subject’s heels and connected to a digital input of the MWX8 DataLog analog-to-digital converter. The converter was fixed at the subject’s hips level by an elastic belt. Elastic bands placed around the subject’s thighs made sure cables remained fixed and did not disturb the gait performance. A digital button was also connected to the converter through a secondary digital input and eventually pressed by the subject at specific time points. The Samsung Galaxy S4 mini was firmly placed at the subject’s lower back through the elastic belt. The author SP gave informed consent for the publication of this image.

Figure 3

Condition-by-condition gait velocity. A condition-by-condition population average (N = 14) profile with standard deviation error bars. Average gait velocity decreases in the two dual-task conditions with respect to the single-task condition. Statistically significant paired-samples t-test corrected for multiple comparisons (Bonferroni, ×3) are highlighted with *(ST vs. DT_i with i = 1, 2) and/or **(DT1 vs. DT2). Detailed results are reported in Table 1.

Figure 4

Group-level time-frequency analyses across conditions for Cz electrode. All subjects (N = 14) average time (x axis)—frequency (y axis) representations of the spectral power of the Cz electrode are here reported for each condition (first row: single-task walking; second row: dual-task1 walking; third row: dual-task2 walking). Two baseline approaches have been used: on the left hand side, the log spectrum of a 3 min period of resting state standing still with eyes-open was used; on the right hand side, the mean gait cycle log spectrum was employed. Color-bars (dB) are constant across conditions within each baseline approach and report increase (values >0, warm-color coded) and decrease (values <0, cold-color coded) of power spectrum with respect to each specific baseline. Group-level significance was calculated via bootstrapping method and FDR correction for multiple comparisons (p < 0.05) according to Wagner et al. (2012). A white mask was applied on those time-frequency bins (i.e., pixels) that did not pass the statistical test.

Figure 5

Grand-average Power Spectral Density (PSD) across conditions in each frequency of interest (FOI). Topographical representations of all subjects (N = 14) average PSD across conditions describes high (warm-color coded) and low (cold-color coded) intensities of PSD (color-bar (dB) is constant across conditions and frequency bands).

Figure 6

Non-parametric cluster-based permutation test comparing PSD in ST vs. Baseline resting state standing still with eyes open. Topographical maps are color-coded according to the permutation tests t-values resulted from the comparison of PSD between single-task walking (ST) and Resting-State (i.e., Baseline). Clusters of electrodes whose PSD is significantly different between the two conditions are highlighted in *(p < 0.002 after Bonferroni correction). In the α frequency band, a general decrease of PSD activity is reported over the whole brain during single-task walking with respect to baseline. In the β frequency band, a decreased PSD activity occurs in a wide cluster including right-frontal-, bilateral-central- and bilateral parietal areas during single-task walking in comparison to baseline.

Figure 7

Non-parametric cluster-based permutation test comparing PSD in DT1 vs. ST. Topographical maps are color-coded according to the permutation tests t-values resulted from the comparison of PSD between dual-task1 walking (DT1) and single-task walking (ST). Clusters of electrodes whose PSD is significantly different between the two conditions are highlighted in *(p < 0.002 after Bonferroni correction). In the θ frequency band, an increased PSD activity occurs in a left frontal and in a right occipital-parietal cluster of electrodes during DT1 with respect to ST. In the β frequency band, an increased PSD activity occurs in a right occipital-parietal cluster of electrodes during DT1 in comparison to ST.

Figure 8

Non-parametric cluster-based permutation test comparing PSD in DT2 vs. DT1. Topographical maps are color-coded according to the permutation tests t-values resulted from the comparison of PSD between dualtask2 walking (DT2) and single-task walking (ST). Clusters of electrodes whose PSD is significantly different between the two conditions are highlighted in *(p < 0.002 after Bonferroni correction). In the β frequency band, a decreased PSD activity occurs in a wide cluster of electrodes extending from left-central frontal-temporal regions to right occipital-parietal areas during DT2 with respect to DT1.