NRS Mental Health Network Annual Scientific Meeting 2021 Nov 02, 2021 09:00 AM - 05:00 PM — Royal College of Physicians, Edinburgh (and online)
SRS Autumn Meeting 2021 Nov 12, 2021 08:30 AM - 04:00 PM — Dundee


SINAPSE experts from around Scotland have developed ten online modules designed to explain medical imaging. They are freely available and are intended for non-specialists.

Edinburgh Imaging Academy at the University of Edinburgh offers the following online programmes through a virtual learning environment:

Neuroimaging for Research MSc/Dip/Cert

Imaging MSc/Dip/Cert

PET-MR Principles & Applications Cert

Applied Medical Image Analysis Cert

Online Short Courses

SINAPSE Image of the Month: Neural marker of proactive movement control in mobile EEG

March 2021 SINAPSE Image of the Month


Courtesy of Magda Mustile and Dr Magdalena Ietswaart, this image shows data from mobile EEG recorded during real‐world ambulatory obstacle avoidance, with study participants walking along a path while stepping over expected and unexpected obstacles projected on the floor. EEG was recorded with a mobile system as participants negotiated movement control demands across four conditions: a "no adjustment" condition, in which no obstacle was presented and participants simply walked across the room; a "preset adjustment" condition, in which obstacles to be stepped over were present at the start of the trial; a "delayed adjustment" condition, in which passing through an infrared laser beam triggered the presentation of an obstacle on the path, presented 310 cm in front of the participant; and an "immediate adjustment" condition, in which passing through the laser beam triggered the presentation of an obstacle just 160 cm in front of the participant. 

After implementing automatic artefact rejection procedures to identify and remove non‐brain signals (e.g., movement and muscle artefacts) from the mobile EEG recordings, the remaining data were segmented into epochs relative to the step over the obstacle (i.e., the 'Crossing' event, which was defined as time 0). 'Planning' (from -1,750 ms to -250 ms) and 'Resetting' (from 250 ms to 1,250 ms) periods were defined, as shown in the figure above, in order to examine temporal dynamics in the spectral power of theta (4-7 Hz) and beta (13-35 Hz) frequency bands across conditions, before and after the obstacle.

Topographic maps of theta power modulation in the figure above show significant effects of condition, scalp location and time across three successive time windows comprising the Planning period.

  • A significantly stronger theta increase was found to occur firstly in the delayed adjustment condition after the obstacle appeared, and decreased more in the immediate compared to preset adjustment condition.
  • In the following time window, the theta increase became stronger in the immediate adjustment condition but was still present in the delayed adjustment condition.
  • In the last time window the theta increase was stronger in the immediate adjustment condition, but the decrease was stronger in the delayed and preset adjustment conditions.

These analyses revealed that the increase in theta power during the Planning phase was largest when participants had less time and space available to change their gait before stepping over an obstacle (i.e., in the immediate adjustment condition). By contrast, this modulation was substantially absent when participants could see the obstacle in advance (i.e., in the preset adjustment condition). The pattern across conditions strongly suggests that increases in frontal theta observed during walking mark a proactive cognitive control mechanism that is engaged in response to unexpected obstacles. Furthermore, the temporal dynamics of theta link the increase in power to the appearance of the obstacle; mobile EEG recorded during real‐world walking shows that motor plans are updated as soon as an upcoming obstacle appears, rather than when the obstacle is reached.


The image is taken from a recent study published in European Journal of Neuroscience:

Mustile M, Kourtis D, Ladouce S, Learmonth G, Edwards MG, Donaldson DI, Ietswaart M. Mobile EEG reveals functionally dissociable dynamic processes supporting real‐world ambulatory obstacle avoidance: Evidence for early proactive control. Eur J Neurosci. 2021; 00:1-14.

  • The study is summarised in the following graphical abstract:


The development of mobile EEG technology means it is now possible to monitor the brain in complex real‐world environments. Here we use this approach to reveal the neuro‐cognitive processes that allow humans to negotiate an obstacle while walking. Time‐frequency analysis of EEG data identifies distinct neural markers, reflecting the different cognitive aspects of obstacle avoidance. Our mobile cognition approach allows us to arbitrate between competing theoretical accounts of cognitive control, while paving the way for clinical applications.