Inferring the topology of a network using the knowledge of the signals of each of the interacting units is key to understanding real-world systems. One way to address this problem is using datadriven methods like cross-correlation or mutual information. However, these measures lack the ability to distinguish the direction of coupling. Here, we use a rank-based nonlinear interdependence measure originally developed for pairs of signals. This measure not only allows one to measure the strength but also the direction of the coupling. Our results for a system of coupled Lorenz dynamics show that we are able to consistently infer the underlying network for a subrange of the coupling strength and link density. Furthermore, we report that the addition of dynamical noise can benefit the reconstruction. Finally, we show an application to multichannel electroencephalographic recordings from an epilepsy patient.

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The application of non-linear signal analysis techniques to biomedical data is key to improve our knowledge about complex physiological and pathological processes. In particular, the use of non-linear techniques to study electroencephalographic (EEG) recordings can provide an advanced characterization of brain dynamics. In epilepsy these dynamics are altered at different spatial scales of neuronal organization. We therefore apply non-linear signal analysis to EEG recordings from epilepsy patients derived with intracranial hybrid electrodes, which are composed of classical macro contacts and micro wires. Thereby, these electrodes record EEG at two different spatial scales. Our aim is to test the degree to which the analysis of the EEG recorded at these different scales allows us to characterize the neuronal dynamics affected by epilepsy. For this purpose, we retrospectively analyzed long-term recordings performed during five nights in three patients during which no seizures took place. As a benchmark we used the accuracy with which this analysis allows determining the hemisphere that contains the seizure onset zone, which is the brain area where clinical seizures originate. We applied the surrogate-corrected non-linear predictability score (ψ), a non-linear signal analysis technique which was shown previously to be useful for the lateralization of the seizure onset zone from classical intracranial EEG macro contact recordings. Higher values of ψ were found predominantly for signals recorded from the hemisphere containing the seizure onset zone as compared to signals recorded from the opposite hemisphere. These differences were found not only for the EEG signals recorded with macro contacts, but also for those recorded with micro wires. In conclusion, the information obtained from the analysis of classical macro EEG contacts can be complemented by the one of micro wire EEG recordings. This combined approach may therefore help to further improve the degree to which quantitative EEG analysis can contribute to the diagnostics in epilepsy patients.

Background Wellness is increasingly recognized as an important component of graduate medical education. However, there are limited data regarding how wellness initiatives are enacted in practice. This study aimed to survey emergency medicine (EM) residency programs to identify current, previous, and planned wellness initiatives as well as barriers to implementation and resources utilized. Methods This was a cross‐sectional survey study performed from November 2019 through January 2020. A literature search was performed to identify existing published wellness interventions and existing barriers, and these interventions and barriers were compiled to create a survey. The survey was piloted among five program directors and assistant program directors in person with feedback directly incorporated into the survey. The survey was sent to program leadership at all 223 Accreditation Council for Graduate Medical Education–accredited EM residency programs across the United States. Results Of the programs surveyed, 95 (42.6%) were included. The most common current wellness interventions reported were resident retreats (91%), group events (90%), formal mentorship (74%), and wellness committees (66%). Reported factors that contributed to the successful implementation of wellness interventions were faculty involvement (78%), resident involvement (78%), department chair support (51%), institutional support (44%), and financial support (36%). Lack of financial support (65%) and limited time (62%) were the most commonly reported barriers that prevented the implementation of wellness interventions. Conclusions Resident wellness is an important aspect of residency training. Survey respondents generally perceived that wellness interventions were associated with wellness improvement. Successful programs have financial, institutional, and chair support.

Supraventricular tachycardia is a common emergency department (ED) pathology that frequently leads to hospital admission, but this may not be necessary in all cases. Here, we present a supraventricular tachycardia patient who was discharged from the ED after vagal maneuvers. This case demonstrates evidence that judicious emergency physicians can discharge supraventricular tachycardia patients home safely and gives impetus for a data-driven protocol for discharging these patients.