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Interactive programming paradigm for real-time experimentation with remote living matter.

ABSTRACT: Recent advancements in life-science instrumentation and automation enable entirely new modes of human interaction with microbiological processes and corresponding applications for science and education through biology cloud laboratories. A critical barrier for remote and on-site life-science experimentation (for both experts and nonexperts alike) is the absence of suitable abstractions and interfaces for programming living matter. To this end we conceptualize a programming paradigm that provides stimulus and sensor control functions for real-time manipulation of physical biological matter. Additionally, a simulation mode facilitates higher user throughput, program debugging, and biophysical modeling. To evaluate this paradigm, we implemented a JavaScript-based web toolkit, "Bioty," that supports real-time interaction with swarms of phototactic Euglena cells hosted on a cloud laboratory. Studies with remote and on-site users demonstrate that individuals with little to no biology knowledge and intermediate programming knowledge were able to successfully create and use scientific applications and games. This work informs the design of programming environments for controlling living matter in general, for living material microfabrication and swarm robotics applications, and for lowering the access barriers to the life sciences for professional and citizen scientists, learners, and the lay public.

SUBMITTER: Washington P

PROVIDER: S-EPMC6431204 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Interactive programming paradigm for real-time experimentation with remote living matter.

Washington Peter P Samuel-Gama Karina G KG Goyal Shirish S Ramaswami Ashwin A Riedel-Kruse Ingmar H IH

Proceedings of the National Academy of Sciences of the United States of America 20190301 12

Recent advancements in life-science instrumentation and automation enable entirely new modes of human interaction with microbiological processes and corresponding applications for science and education through biology cloud laboratories. A critical barrier for remote and on-site life-science experimentation (for both experts and nonexperts alike) is the absence of suitable abstractions and interfaces for programming living matter. To this end we conceptualize a programming paradigm that provides ...[more]

PMID: 30824592

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Project description:Introduction: Functional magnetic resonance imaging (fMRI) often involves long scanning durations to ensure the associated brain activity can be detected. However, excessive experimentation can lead to many undesirable effects, such as from learning and/or fatigue effects, discomfort for the subject, excessive motion artifacts and loss of sustained attention on task. Overly long experimentation can thus have a detrimental effect on signal quality and accurate voxel activation detection. Here, we propose dynamic experimentation with real-time fMRI using a novel statistically driven approach that invokes early stopping when sufficient statistical evidence for assessing the task-related activation is observed. Methods: Voxel-level sequential probability ratio test (SPRT) statistics based on general linear models (GLMs) were implemented on fMRI scans of a mathematical 1-back task from 12 healthy teenage subjects and 11 teenage subjects born extremely preterm (EPT). This approach is based on likelihood ratios and allows for systematic early stopping based on target statistical error thresholds. We adopt a two-stage estimation approach that allows for accurate estimates of GLM parameters before stopping is considered. Early stopping performance is reported for different first stage lengths, and activation results are compared with full durations. Finally, group comparisons are conducted with both early stopped and full duration scan data. Numerical parallelization was employed to facilitate completion of computations involving a new scan within every repetition time (TR). Results: Use of SPRT demonstrates the feasibility and efficiency gains of automated early stopping, with comparable activation detection as with full protocols. Dynamic stopping of stimulus administration was achieved in around half of subjects, with typical time savings of up to 33% (4 min on a 12 min scan). A group analysis produced similar patterns of activity for control subjects between early stopping and full duration scans. The EPT group, individually, demonstrated more variability in location and extent of the activations compared to the normal term control group. This was apparent in the EPT group results, reflected by fewer and smaller clusters. Conclusion: A systematic statistical approach for early stopping with real-time fMRI experimentation has been implemented. This dynamic approach has promise for reducing subject burden and fatigue effects.

Dataset Information

Interactive programming paradigm for real-time experimentation with remote living matter.

Publications

Interactive programming paradigm for real-time experimentation with remote living matter.

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