ArticleJournal of neural engineering2018
Design strategies for dynamic closed-loop optogenetic neurocontrol in vivo.
Article in Journal of neural engineering, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed.
- Bridging Model and Experiment in Systems Neuroscience with Cleo: The Closed-Loop, Electrophysiology, and Optophysiology Simulation Testbed.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026Article
- Closed-loop optogenetic control of cell biology enables outcome-driven microscopy.Nature communications · 2025Article
- Bridging model and experiment in systems neuroscience with Cleo: the Closed-Loop, Electrophysiology, and Optophysiology simulation testbed.bioRxiv : the preprint server for biology · 2025Article
- Prioritized learning of cross-population neural dynamics.Journal of neural engineering · 2025Article
- Brain-computer interfaces for neuropsychiatric disorders.Nature reviews bioengineering · 2024Article
- Event detection and classification from multimodal time series with application to neural data.Journal of neural engineering · 2024Article
- Dynamic corticothalamic modulation of the somatosensory thalamocortical circuit during wakefulness.Nature communications · 2024Article
- Multimodal subspace identification for modeling discrete-continuous spiking and field potential population activity.Journal of neural engineering · 2024Article
- Unsupervised learning of stationary and switching dynamical system models from Poisson observations.Journal of neural engineering · 2023Article
- Bayesian target optimisation for high-precision holographic optogenetics.bioRxiv : the preprint server for biology · 2023Article
- Delayed closed-loop neurostimulation for the treatment of pathological brain rhythms in mental disorders: a computational study.Frontiers in neuroscience · 2023Article
- Predictive neuromodulation of cingulo-frontal neural dynamics in major depressive disorder using a brain-computer interface system: A simulation study.Frontiers in computational neuroscience · 2023Article
- A field-programmable gate array (FPGA)-based data acquisition system for closed-loop experiments.The Review of scientific instruments · 2022Article
- Thalamic bursting and the role of timing and synchrony in thalamocortical signaling in the awake mouse.Neuron · 2022Article
- The Future of Neurotoxicology: A Neuroelectrophysiological Viewpoint.Frontiers in toxicology · 2021Article
- Improving scalability in systems neuroscience.Neuron · 2021Review
- Thalamic state influences timing precision in the thalamocortical circuit.Journal of neurophysiology · 2021Article
- Modelling and prediction of the dynamic responses of large-scale brain networks during direct electrical stimulation.Nature biomedical engineering · 2021Article
- State-space optimal feedback control of optogenetically driven neural activity.Journal of neural engineering · 2021Article
- Multiscale low-dimensional motor cortical state dynamics predict naturalistic reach-and-grasp behavior.Nature communications · 2021Article
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5 authors.
Funding
Abstract
objectiveControlling neural activity enables the possibility of manipulating sensory perception, cognitive processes, and body movement, in addition to providing a powerful framework for functionally disentangling the neural circuits that underlie these complex phenomena. Over the last decade, optogenetic stimulation has become an increasingly important and powerful tool for understanding neural circuit function, owing to the ability to target specific cell types and bidirectionally modulate neural activity. To date, most stimulation has been provided in open-loop or in an on/off closed-loop fashion, where previously-determined stimulation is triggered by an event. Here, we describe and demonstrate a design approach for precise optogenetic control of neuronal firing rate modulation using feedback to guide stimulation continuously. APPROACH: Using the rodent somatosensory thalamus as an experimental testbed for realizing desired time-varying patterns of firing rate modulation, we utilized a moving average exponential filter to estimate firing rate online from single-unit spiking measured extracellularly. This estimate of instantaneous rate served as feedback for a proportional integral (PI) controller, which was designed during the experiment based on a linear-nonlinear Poisson (LNP) model of the neuronal response to light. MAIN
resultsThe LNP model fit during the experiment enabled robust closed-loop control, resulting in good tracking of sinusoidal and non-sinusoidal targets, and rejection of unmeasured disturbances. Closed-loop control also enabled manipulation of trial-to-trial variability. SIGNIFICANCE: Because neuroscientists are faced with the challenge of dissecting the functions of circuit components, the ability to maintain control of a region of interest in spite of changes in ongoing neural activity will be important for disambiguating function within networks. Closed-loop stimulation strategies are ideal for control that is robust to such changes, and the employment of continuous feedback to adjust stimulation in real-time can improve the quality of data collected using optogenetic manipulation.
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