Background: Burst suppression occurs in the EEG during coma and under general anaesthesia. It has been assumed that burst suppression represents a deeper state of anaesthesia from which it is more difficult to recover. This has not been directly demonstrated, however. Here, we test this hypothesis directly by assessing relationships between EEG suppression in human volunteers and recovery of consciousness. Methods: We recorded the EEG of 27 healthy humans (nine women/18 men) anaesthetised with isoflurane 1.3 minimum alveolar concentration (MAC) for 3 h. Periods of EEG suppression and non-suppression were separated using principal component analysis of the spectrogram. After emergence, participants completed the digit symbol substitution test and the psychomotor vigilance test. Results: Volunteers demonstrated marked variability in multiple features of the suppressed EEG. In order to test the hypothesis that, for an individual subject, inclusion of features of suppression would improve accuracy of a model built to predict time of emergence, two types of models were constructed: one with a suppression-related feature included and one without. Contrary to our hypothesis, Akaike information criterion demonstrated that the addition of a suppression-related feature did not improve the ability of the model to predict time to emergence. Furthermore, the amounts of EEG suppression and decrements in cognitive task performance relative to pre-anaesthesia baseline were not significantly correlated. Conclusions: These findings suggest that, in contrast to current assumptions, EEG suppression in and of itself is not an important determinant of recovery time or the degree of cognitive impairment upon emergence from anaesthesia in healthy adults.

Background As evidenced by the further reduction in access to testing during the COVID-19 pandemic, there is an urgent, growing need for remote cognitive assessment for individuals with cognitive impairment. The Neurotrack Cognitive Battery (NCB), our response to this need, was evaluated for its temporal reliability and stability as part of ongoing validation testing. Objective The aim of this study is to assess the temporal reliability of the NCB tests (5 total) across a 1-week period and to determine the temporal stability of these measures across 3 consecutive administrations in a single day. Methods For test-retest reliability, a range of 29-66 cognitively healthy participants (ages 18-68 years) completed each cognitive assessment twice, 1 week apart. In a separate study, temporal stability was assessed using data collected from 31 different cognitively healthy participants at 3 consecutive timepoints in a single day. Results Correlations for the assessments were between 0.72 and 0.83, exceeding the standard acceptable threshold of 0.70 for temporal reliability. Intraclass correlations ranged from 0.60 to 0.84, indicating moderate to good temporal stability. Conclusions These results highlight the NCB as a brief, easy-to-administer, and reliable assessment for remote cognitive testing. Additional validation research is underway to determine the full magnitude of the clinical utility of the NCB.

Background Psychiatric symptomatology, including anxiety, partially comprise the clinical prodrome of dementia. Moreover, increased anxiety may represent a risk factor associated with neurodegenerative disease. Efficient, longitudinal measurement of anxiety remains difficult with traditional paper‐pencil measures. As few digital measures of anxiety symptomatology exist, we aimed to develop and validate a digitally native, efficient and repeatable, anxiety survey to measure self‐reported anxiety in adults: the Digital Choice Anxiety Survey (DCAS). Method Development of the DCAS included three studies: Study one included adult participants (n=407) who completed a larger set of anxiety questions, alongside the Penn State Worry Questionnaire (PSWQ) and General Anxiety Disorder 7‐item (GAD‐7) survey. Factor analysis then reduced the larger set of DCAS questions and investigated convergent validity and accuracy of the DCAS. Study two recruited a sub‐sample of the original cohort (n=70) who completed the reduced DCAS survey to investigate convergent validity with the Geriatric Depression Scale (GDS). Study three recruited a separate sample of adults (n =58), who were administered the DCAS at baseline and again approximately two weeks after initial administration to examine test‐retest reliability. Result Study one: Mean participant age was 42.92±12.86 years. After removing questions with a Spearman’s correlation greater than or equal to 0.6, DCAS was shortened from 20 to 7 items. The 7 items showed strong internal reliability (Cronbach’s α=0.86), with a one factor solution found utilizing factor analysis (all factors r>0.56). There were positive associations with the PSWQ and GAD‐7 (r=0.82 & r=0.85), with overall accuracy of 0.93 for moderate anxiety on both PSWQ & GAD‐7. Study two: Mean participant age was 48.94±14.63 years. A positive association was found between the 7‐item DCAS and the GDS‐15 (r=0.58, p<0.01). Study three: Mean participant age was 54.79±12.53 years. Participants completed the DCAS an average of 11.7 days apart (SD=1.2) and showed robust test‐retest reliability (Pearson’s r=0.81). Conclusion This study provides evidence for psychometric validity and reliability of the DCAS. Follow‐up studies will investigate performance of the DCAS on clinically characterized populations and examine participant‐associated meta‐data.

Background: Globally, the prevalence of Alzheimer's disease is expected to triple by 2050. Additionally, as COVID-19 has accelerated the urgency for remote neuropsychological assessment, the development of easily accessible and valid remote methods of assessments are critical for continued monitoring of cognitive health. In response to this clinical and scientific need, we investigate the use of the Neurotrack assessment suite as a remote digital cognitive assessment platform. Method:As part of an ongoing study, 9 patients diagnosed with AD (Mean age = 75.6, 55% female) and 9 cognitively healthy controls (Mean age = 75.6, 44% female) were assessed using three exams from the Neurotrack assessment suite which were designed to assess 1) processing speed, 2) associative learning and 3) associative and recognition memory. Independent samples t-tests were conducted to examine differences in exams scores between the two groups.Results: There were significant differences observed in processing speed (p=.004), associative learning (p=.001), and associative memory performance (p=.03) between patients with AD and cognitive healthy controls. There was no difference in recognition memory (p=.47). Conclusion:The Neurotrack Assessment Suite appears to be a promising method for remote cognitive testing. Further investigation of the efficacy of this platform as a valid and easily accessible assessment tool is currently underway.