Commanding or being a simple intermediary: how does it affect moral behavior and related brain mechanisms?

History has shown that fractioning operations between several individuals along a hierarchical chain allows diffusing responsibility between components of the chain, which has the potential to disinhibit antisocial actions. Here, we present two studies, one using fMRI (Study 1) and one using EEG (Study 2), designed to help understand how commanding or being in an intermediary position impacts the sense of agency and empathy for pain. In the age of military drones, we also explored whether commanding a human or robot agent influences these measures. This was done within a single behavioral paradigm in which participants could freely decide whether or not to send painful shocks to another participant in exchange for money. In Study 1, fMRI reveals that activation in social cognition and empathy-related brain regions was equally low when witnessing a victim receive a painful shock while participants were either commander or simple intermediary transmitting an order, compared to being the agent directly delivering the shock. In Study 2, results indicated that the sense of agency did not differ between commanders and intermediary, no matter if the executing agent was a robot or a human. However, we observed that the neural response over P3 was higher when the executing agent was a robot compared to a human. Source reconstruction of the EEG signal revealed that this effect was mediated by areas including the insula and ACC. Results are discussed regarding the interplay between the sense of agency and empathy for pain for decision-making.

Sharing individualised template MRI data for MEG source reconstruction: a solution for open data while keeping subject confidentiality

The increasing requirements for adoption of FAIR data management and sharing original research data from neuroimaging studies can be at odds with protecting the anonymity of the research participants due to the person-identifiable anatomical features in the data. We propose a solution to this dilemma for anatomical MRIs used in MEG source analysis. In MEG analysis, the channel-level data is reconstructed to the source-level using models derived from anatomical MRIs. Sharing data, therefore, requires sharing the anatomical MRI to replicate the analysis. The suggested solution is to replace the individual anatomical MRIs with individualised warped templates that can be used to carry out the MEG source analysis and that provide sufficient geometrical similarity to the original participants' MRIs. First, we demonstrate how the individualised template warping can be implemented with one of the leading open-source neuroimaging analysis toolboxes. Second, we compare results from four different MEG source reconstruction methods performed with an individualised warped template to those using the participant's original MRI. While the source reconstruction results are not numerically identical, there is a high similarity between the results for single dipole fits, dynamic imaging of coherent sources beamforming, and atlas-based virtual channel beamforming. There is a moderate similarity between minimum-norm estimates, as anticipated due to this method being anatomically constrained and dependent on the exact morphological features of the cortical sheet. We also compared the morphological features of the warped template to those of the original MRI. These showed a high similarity in grey matter volume and surface area, but a low similarity in the average cortical thickness and the mean folding index within cortical parcels. Taken together, this demonstrates that the results obtained by MEG source reconstruction can be preserved with the warped templates, whereas the anatomical and morphological fingerprint is sufficiently altered to protect the anonymity of research participants. In cases where participants consent to sharing anatomical MRI data, it remains preferable to share the original defaced data with an appropriate data use agreement. In cases where participants did not consent to share their MRIs, the individualised warped MRI template offers a good compromise in sharing data for reuse while retaining anonymity for those research participants.

Cortical Source Analysis of Event-Related Potentials: A Developmental Approach

Cortical source analysis of electroencephalographic (EEG) signals has become an important tool in the analysis of brain activity. The aim of source analysis is to reconstruct the cortical generators (sources) of the EEG signal recorded on the scalp. The quality of the source reconstruction relies on the accuracy of the forward problem, and consequently the inverse problem. An accurate forward solution is obtained when an appropriate imaging modality (i.e., structural magnetic resonance imaging – MRI) is used to describe the head geometry, precise electrode locations are identified with 3D maps of the sensor positions on the scalp, and realistic conductivity values are determined for each tissue type of the head model. Together these parameters contribute to the definition of realistic head models. Here, we describe the steps necessary to reconstruct the cortical generators of the EEG signal recorded on the scalp. We provide an example of source reconstruction of event-related potentials (ERPs) during a face-processing task performed by a 6-month-old infant. We discuss the adjustments necessary to perform source analysis with measures different from the ERPs. The proposed pipeline can be applied to the investigation of different cognitive tasks in both younger and older participants.