Serotonin is implicated in multiple executive functions including goal-directed learning, cognitive flexibility, response inhibition and emotional regulation. These functions are impaired in several psychiatric disorders, such as depression and obsessive–compulsive disorder. We tested the cognitive effects of the selective serotonin reuptake inhibitor escitalopram, using an acute and clinically relevant dose (20 mg), in 66 healthy male and female volunteers in a double-blind, placebo-controlled study. Participants performed a cognitive test battery including a probabilistic and reversal learning task, the CANTAB intra-dimensional/extra-dimensional shift test of cognitive flexibility, a response inhibition task with interleaved stop-signal and No-Go trials and tasks measuring emotional processing. We showed that acute escitalopram administration impaired learning and cognitive flexibility, but improved the ability to inhibit responses in stop-signal trials while leaving unaffected acute emotional processing. Our findings suggest a dissociation of effects of acute escitalopram on cognitive functions, possibly mediated by differential modulation of brain serotonin levels in distinct functional neural circuits.

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Background: Digital technologies have the potential to provide objective and precise tools to detect depression-related symptoms. Deployment of digital technologies in clinical research can enable collection of large volumes of clinically relevant data that may not be captured using conventional psychometric questionnaires and patient-reported outcomes. Rigorous methodology studies to develop novel digital endpoints in depression are warranted.Objective: We conducted an exploratory, cross-sectional study to evaluate several digital technologies in subjects with major depressive disorder (MDD) and persistent depressive disorder (PDD), and healthy controls. The study aimed at assessing utility and accuracy of the digital technologies as potential diagnostic tools for unipolar depression, as well as correlating digital biomarkers to clinically validated psychometric questionnaires in depression.Methods: A cross-sectional, non-interventional study of 20 participants with unipolar depression (MDD and PDD/dysthymia) and 20 healthy controls was conducted at the Centre for Human Drug Research (CHDR), the Netherlands. Eligible participants attended three in-clinic visits (days 1, 7, and 14), at which they underwent a series of assessments, including conventional clinical psychometric questionnaires and digital technologies. Between the visits, there was at-home collection of data through mobile applications. In all, seven digital technologies were evaluated in this study. Three technologies were administered via mobile applications: an interactive tool for the self-assessment of mood, and a cognitive test; a passive behavioral monitor to assess social interactions and global mobility; and a platform to perform voice recordings and obtain vocal biomarkers. Four technologies were evaluated in the clinic: a neuropsychological test battery; an eye motor tracking system; a standard high-density electroencephalogram (EEG)-based technology to analyze the brain network activity during cognitive testing; and a task quantifying bias in emotion perception.Results: Our data analysis was organized by technology – to better understand individual features of various technologies. In many cases, we obtained simple, parsimonious models that have reasonably high diagnostic accuracy and potential to predict standard clinical outcome in depression.Conclusion: This study generated many useful insights for future methodology studies of digital technologies and proof-of-concept clinical trials in depression and possibly other indications.

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Background: Current cognitive and functional assessments of patients with cognitive impairment and dementia have well understood limitations including high test:re-test variability, sparse data collection in clinic environments that may not reflect 'real life' performance, and assessment tools being language, education and culture sensitive. Continuous patient data collection using wearable devices (e.g. wristbands/wristwatches) measuring factors such as activity and sleep, may provide future digital biomarkers that are more sensitive than current approaches especially for assessing function in clinical trials. It is therefore important to evaluate acceptance and tolerability of such devices for patients and caregivers, determine how such continuous data collection may fit with conventional clinical measures, and establish the technical and regulatory requirements for GCP compliance. Methods: We undertook SWOT analyses on: (1)study designs most suited to evaluate the use of wearables for clinical data collection; (2) acceptability and tolerability of a commercially available wearable device [1]; and (3)technical and regulatory challenges in in recording the study data. Using qualitative methods including semi-structured and free discussions, we held focus groups with stakeholder representatives (people with dementia and caregivers; n¼12) to explore these issues. Results: Strengths: prospect of participating in such studies; transfer and storage of data from wearables via mobile devices; and tolerability of such devices for either clinical care or research purposes. Weaknesses: potential for non-adherence with the device, particularly at night; difficulty in putting devices on without help; and loss of connectivity for data collection. The Cygnus project [2] will soon start, and deploy these technologies in a symptomatic, community population with cognitive impairment and their care-givers. Conclusions: The use of wearables for continuous clinical data collection is feasible and potentially tolerated by patients with cognitive impairment and dementia. Data security, authentication and validation challenges remain for GCP compliance but patients did not raise concerns about impact on their privacy. Studies like Cygnus are now needed to evaluate prospectively the tolerability of wearable devices and whether meaningful digital functional biomarkers can be generated from the data; further work is required to establish the regulatory path for such devices providing functional endpoints in clinical trials.[1] Withings Activity Pop [2] Cygnus, Innovate UK Grant no.102159.Background: Clinical and research assessments of cognition, mood and behaviour provide validated snapshots of functioning at specific time points. However, depression and mild cognitive impairment exhibit fluctuations which are challenging to quantify, but impact on quality of life and ability to perform daily tasks. The identification of these fluctuations has the potential to provide ecologically relevant outcomes for clinical research, complementing i...