EEG beta suppression and low gamma modulation are different elements of human upright walking

Research in brain-computer interfaces has achieved impressive progress towards implementing assistive technologies for restoration or substitution of lost motor capabilities, as well as supporting technologies for able-bodied subjects. Notwithstanding this progress, effective translation of these interfaces from proof-of concept prototypes into reliable applications remains elusive. As a matter of fact, most of the current BCI systems cannot be used independently for long periods of time by their intended end-users. Multiple factors that impair achieving this goal have already been identified. However, it is not clear how do they affect the overall BCI performance or how they should be tackled. This is worsened by the publication bias where only positive results are disseminated, preventing the research community from learning from its errors. This paper is the result of a workshop held at the 6th International BCI meeting in Asilomar. We summarize here the discussion on concrete research avenues and guidelines that may help overcoming common pitfalls and make BCIs become a useful alternative communication device.

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“…Some attempts to enhance the interpretability of brain oscillations are already ongoing (e.g. [90,91]).…”

Section: Signal Processing and Decodingmentioning

confidence: 99%

Heading for new shores! Overcoming pitfalls in BCI design

Chavarriaga

Fried-Oken²,

Kleih

et al. 2016

Brain-Computer Interfaces

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“…Our laboratory has recorded electrocortical spectral fluctuations during treadmill walking in healthy, young adults (Gwin et al, 2011; Sipp et al, 2013). Other groups have also proved the feasibility of measuring scalp electrocortical signals during human walking, at speeds ranging from 0.42 m/s to 1.9 m/s, to provide insight into brain function (Gramann et al, 2010; Cheron et al, 2012; Lau et al, 2012; Severens et al, 2012; Wagner et al, 2012; Seeber et al, 2014; Seeber et al, 2015). …”

Section: Introductionmentioning

confidence: 99%

Isolating gait-related movement artifacts in electroencephalography during human walking

et al. 2015

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Objective High-density electroencephelography (EEG) can provide insight into human brain function during real-world activities with walking. Some recent studies have used EEG to characterize brain activity during walking, but the relative contributions of movement artifact and electrocortical activity have been difficult to quantify. We aimed to characterize movement artifact recorded by EEG electrodes at a range of walking speeds and to test the efficacy of artifact removal methods. We also quantified the similarity between movement artifact recorded by EEG electrodes and a head-mounted accelerometer. Approach We used a novel experimental method to isolate and record movement artifact with EEG electrodes during walking. We blocked electrophysiological signals using a nonconductive layer (silicone swim cap) and simulated an electrically conductive scalp on top of the swim cap using a wig coated with conductive gel. We recorded motion artifact EEG data from nine young human subjects walking on a treadmill at speeds from 0.4–1.6 m/s. We then tested artifact removal methods including moving average and wavelet-based techniques. Main Results Movement artifact recorded with EEG electrodes varied considerably, across speed, subject, and electrode location. The movement artifact measured with EEG electrodes did not correlate well with head acceleration. All of the tested artifact removal methods attenuated low-frequency noise but did not completely remove movement artifact. The spectral power fluctuations in the movement artifact data resembled data from some previously published studies of EEG during walking. Significance Our results suggest that EEG data recorded during walking likely contains substantial movement artifact that: cannot be explained by head accelerations; varies across speed, subject, and channel; and cannot be removed using traditional signal processing methods. Future studies should focus on more sophisticated methods for removing of EEG movement artifact to advance the field.

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“…The beta suppression may be related to initiation and execution of movement, while the prefrontal beta increase to cognitive top-down control. Seeber et al (2014) found that during active walking the upper mu (10–12 Hz) and beta (18–30 Hz) oscillations were suppressed compared to upright standing and the significant beta ERD activity was located focally in central sensorimotor areas. They also found that low gamma (24–40 Hz) amplitudes were modulated related to the gait phase.…”

Section: Introductionmentioning

confidence: 99%

BrainCycles: Experimental Setup for the Combined Measurement of Cortical and Subcortical Activity in Parkinson's Disease Patients during Cycling

Gratkowski

Storzer

Butz

et al. 2017

Front. Hum. Neurosci.

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Recently, it has been demonstrated that bicycling ability remains surprisingly preserved in Parkinson's disease (PD) patients who suffer from freezing of gait. Cycling has been also proposed as a therapeutic means of treating PD symptoms, with some preliminary success. The neural mechanisms behind these phenomena are however not yet understood. One of the reasons is that the investigations of neuronal activity during pedaling have been up to now limited to PET and fMRI studies, which restrict the temporal resolution of analysis, and to scalp EEG focused on cortical activation. However, deeper brain structures like the basal ganglia are also associated with control of voluntary motor movements like cycling and are affected by PD. Deep brain stimulation (DBS) electrodes implanted for therapy in PD patients provide rare and unique access to directly record basal ganglia activity with a very high temporal resolution. In this paper we present an experimental setup allowing combined investigation of basal ganglia local field potentials (LFPs) and scalp EEG underlying bicycling in PD patients. The main part of the setup is a bike simulator consisting of a classic Dutch-style bicycle frame mounted on a commercially available ergometer. The pedal resistance is controllable in real-time by custom software and the pedal position is continuously tracked by custom Arduino-based electronics using optical and magnetic sensors. A portable bioamplifier records the pedal position signal, the angle of the knee, and the foot pressure together with EEG, EMG, and basal ganglia LFPs. A handlebar-mounted display provides additional information for patients riding the bike simulator, including the current and target pedaling rate. In order to demonstrate the utility of the setup, example data from pilot recordings are shown. The presented experimental setup provides means to directly record basal ganglia activity not only during cycling but also during other movement tasks in patients who have undergone DBS treatment. Thus, it can facilitate studies comparing bicycling and walking, to elucidate why PD patients often retain the ability to bicycle despite severe freezing of gait. Moreover it can help clarifying the mechanism through which cycling may have therapeutic benefits.

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EEG beta suppression and low gamma modulation are different elements of human upright walking

Cited by 175 publications

References 49 publications

Heading for new shores! Overcoming pitfalls in BCI design

Heading for new shores! Overcoming pitfalls in BCI design

Isolating gait-related movement artifacts in electroencephalography during human walking

BrainCycles: Experimental Setup for the Combined Measurement of Cortical and Subcortical Activity in Parkinson's Disease Patients during Cycling

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