A new paper led by Luke Tait is published on Human Brain mapping. This study systematically evaluated the performance of six commonly-used source reconstruction algorithms. Using human resting-state MEG, we compared the algorithms using quantitative metrics, including resolution properties of inverse solutions and explained variance in sensor-level data. Next, we proposed a data-driven approach to reduce the atlas from the Human Connectome Project’s multi-modal parcellation of the human cortex based on metrics such as MEG signal-to-noise-ratio and resting-state functional connectivity gradients. This procedure produced a reduced cortical atlas with 230 regions, optimized to match the spatial resolution and the rank of MEG data from the current generation of MEG scanners.

Our results show that there is no “one size fits all” algorithm, and make recommendations on the appropriate algorithms depending on the data and aimed analyses. Our comprehensive comparisons and recommendations can serve as a guide for choosing appropriate methodologies in future studies of resting-state MEG.

The paper is now available online.

Wojciech Zajkowski passed his viva last month. Big congratulations and we wish Wojciech all the best in his new reserach fellow position.

Thin month we welcome a new member Nikolay Petrov. Nikolay will work on our internet-based behavioural experiments.

Also, some lab members are finally able to catch up face-to-face after over 15 months of COVID restrictions.

A new paper led by Marinho Lopes is published on Clinical Neurophysiology. The study applied the brain network ictogenicity framework to quantify the inherent propensity to generate seizures from resting-state MEG recordings. We found that resting-state MEG functional networks from people with epilepsy are characterized by a higher propensity to generate seizures than those from healthy volunteers, with a classification accuracy of 73%. This sensitive computational modelling approach could in future aid diagnosis.

The paper is now available online.

We carry on our research while everyone has adapted to work from home. Dominik has passed his PhD viva, a big achievement in a challenging year. Big congratulations Dr Krzeminski! Luke has started his new job at the University of Birmingham while maintains our close collaborations on several ongoing projects. We really appreciate their important contributions in the last few years and wish them all the best in their future careers.

A new paper led by Wojciech Zajkowski and Dominik Krezeminski is published on Computational Brain & Behavior. This study examined the neurocognitive processes underlying such voluntary decisions by integrating cognitive modelling of behavioral responses and EEG recordings in a probabilistic reward task. Human participants performed binary choices between pairs of unambiguous cues associated with identical reward probabilities at different levels. Higher reward probability accelerated RT, and participants chose one cue faster and more frequent over the other at each probability level. The behavioral effects on RT persisted in simple reactions to single cues. By using hierarchical Bayesian parameter estimation for an accumulator model, we showed that the probability and preference effects were independently associated with changes in the speed of evidence accumulation, but not with visual encoding or motor execution latencies. Time-resolved MVPA of EEG-evoked responses identified significant representations of reward certainty and preference as early as 120 ms after stimulus onset, with spatial relevance patterns maximal in middle central and parietal electrodes. Furthermore, EEG-informed computational modelling showed that the rate of change between N100 and P300 event-related potentials modulated accumulation rates on a trial-by-trial basis. Our findings suggest that reward probability and spontaneous preference collectively shape voluntary decisions between equal options, providing a mechanism to prevent indecision or random behavior.

The paper is now available online.