Analysis of EEG microstates as biomarkers in neuropsychological processes - Review

Microstate analysis is a spatiotemporal method where instantaneous scalp potential topography represents the current state of the brain. The temporal evolution of these scalp topographies gives an understanding of quasi-stable periods of long-range coherence between distant electrodes, reflecting functional coordination within large-scale cortical networks. It has been proven potential in identification and characterization of neurophysiological indicators associated with neuropsychiatric conditions. Changes in microstates connected to symptoms and cognitive impairments of neuropsychiatric conditions. It is useful in the study of cognitive processes and disorders related to memory. Researchers may probe into the relationships between microstates and other cognitive processes, such as memory retrieval and encoding. This is a tool for clinicians to enhance the precision of diagnosis and inform possibilities for treatment by acquiring information regarding individual diversity in microstates could lead to tailored medical methods. Customizing treatment according to a patient's microstate patterns could improve the efficacy of treatment. The papers selected for the review span a broad-spectrum including memory related disorders, psychiatry and neurological disorders. A section in the review article has been dedicated to source localization of EEG microstates. The selection of review papers shed light on the importance and huge potential of application of EEG microstate analysis in various neuropsychological processes. The review concludes with the need for standardization of microstate analysis. It suggests the incorporation of widely accepted machine learning techniques for increasing the accuracy, reliability and acceptability of microstate analysis as reliable biomarkers for neurological conditions in the future.

Efficacy of an online course in developing competency for prescribing balanced diet by medical students: A non - inferiority trial

Background

In the COVID era, medical education has been hit hard. Paradoxically, the need for health professionals has increased. Online methods are being widely used, but its efficacy is rarely measured.

Objectives

This study was conducted to find the efficacy of an online course in developing competency among medical students to prescribe balanced diet.

Methods

An online module was hosted at https://drzinia.moodlecloud.com/. A noninferiority trial was conducted among voluntary participants of the third MBBS students, in 2019. Stratified block randomization was done, so that ten students were allocated to the intervention arm of online sessions and ten students were allocated to the control arm of classroom sessions. Pretest assessments, seven assessments related to sessions conducted, and a postassessment were done. Generalized estimating equations were done to adjust for the effects of other confounders and see whether the intervention was a significant determinant of ability to prescribe balanced diet.

Results

Baseline variables were comparable in the two groups. The pretest scores were not significantly different in the two groups. The mean total marks scored by the online group (47.33/70) was not significantly different (t=0.68; p=0.50) from that of the class room group (45.70/70). The posttest scores were significantly higher than the pretest scores. Ninety-percent of students in the online course agreed that they could effectively learn through an online course.

Conclusion

Online teaching is effective to learn the prescription of balanced diet. Similar efforts in other domains can make medical education evidence based in the current scenario.