Design strategies for dynamic closed-loop optogenetic neurocontrol<i>in vivo</i>

Bolus, Michael; Willats, A.; Whitmire, Clarissa J.; Rozell, Christopher J.; Stanley, Garrett B.

doi:10.1088/1741-2552/aaa506

Cited by 55 publications

(75 citation statements)

References 57 publications

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“…Although spiking activity is the predominant signal used to study brain mechanisms and build brain-machine interfaces (BMIs), the quality of the recorded action potentials often degrades gradually in time. LFP activity is more durable, can augment the usable lifespan of recordings and enhance future BMIs for neural decoding and stimulation 24,41,[60][61][62][63] . Here, we learn the multiscale dynamics in spiking and LFP activity with a data-driven state-space model 6,18,19,21,22,42,46,47,49,53,60,[62][63][64][65][66][67][68] but by leveraging an unsupervised multiscale EM algorithm 42 that can jointly model multiscale spiking and LFP activities together.…”

Section: Discussionmentioning

confidence: 99%

“…LFP activity is more durable, can augment the usable lifespan of recordings and enhance future BMIs for neural decoding and stimulation 24,41,[60][61][62][63] . Here, we learn the multiscale dynamics in spiking and LFP activity with a data-driven state-space model 6,18,19,21,22,42,46,47,49,53,60,[62][63][64][65][66][67][68] but by leveraging an unsupervised multiscale EM algorithm 42 that can jointly model multiscale spiking and LFP activities together. Various supervised and unsupervised machine learning algorithms have been developed for state-space models but are instead designed for single-scale activity 6,18,46,47,53,60,[62][63][64][65]68 .…”

Section: Discussionmentioning

confidence: 99%

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Multiscale low-dimensional motor cortical state dynamics predict naturalistic reach-and-grasp behavior

et al. 2021

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Motor function depends on neural dynamics spanning multiple spatiotemporal scales of population activity, from spiking of neurons to larger-scale local field potentials (LFP). How multiple scales of low-dimensional population dynamics are related in control of movements remains unknown. Multiscale neural dynamics are especially important to study in naturalistic reach-and-grasp movements, which are relatively under-explored. We learn novel multiscale dynamical models for spike-LFP network activity in monkeys performing naturalistic reach-and-grasps. We show low-dimensional dynamics of spiking and LFP activity exhibited several principal modes, each with a unique decay-frequency characteristic. One principal mode dominantly predicted movements. Despite distinct principal modes existing at the two scales, this predictive mode was multiscale and shared between scales, and was shared across sessions and monkeys, yet did not simply replicate behavioral modes. Further, this multiscale mode’s decay-frequency explained behavior. We propose that multiscale, low-dimensional motor cortical state dynamics reflect the neural control of naturalistic reach-and-grasp behaviors.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Multiscale low-dimensional motor cortical state dynamics predict naturalistic reach-and-grasp behavior

et al. 2021

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“…This has two major implications: first, closed-loop design could address many of the challenges that arise as experiments become increasingly sophisticated. Closed-loop design will allow for the exploration of otherwise intractable spaces, such as mapping thousands of synaptic connections or estimating higher-order terms of nonlinear stimulus-response functions (Bolus et al, 2018; DiMattina and Zhang, 2013; Grosenick et al, 2015). Second, closed-loop design should enable whole new classes of experiments that could provide insight into cortical dynamics not obtainable with more conventional approaches.…”

Section: Cracking Layers New Tools From the Technical Revolution In Nmentioning

confidence: 99%

Cracking the Function of Layers in the Sensory Cortex

Adesnik

Naka

2018

Neuron

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Summary: Understanding how cortical activity generates sensory perceptions requires a detailed dissection of the function of cortical layers. Despite our relatively extensive knowledge of their anatomy and wiring, we have a limited grasp for what each layer contributes to cortical computation. We need to develop a theory of cortical function that is rooted solidly in each layer’s component cell types and fine circuit architecture, and produces predictions that can be validated by specific perturbations. Here, we briefly review progress toward such a theory, and suggest an experimental roadmap toward this goal. We discuss new methods for the all-optical interrogation of cortical layers, for correlating in vivo function with precise identification of transcriptional cell type, and for mapping local and long range activity in vivo with synaptic resolution. The new technologies that can crack the function of cortical layers are finally on the immediate horizon.

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“…If this issue is successfully addressed, it would become possible to interact with the neural activity in the continuous manner instead of the neuron stimulation with the electrical pulses in a discrete closed-loop fashion. Nowadays, this is achieved by the optogenetic brain stimulation [27,28] with the help of hybrid optoelectronic interfaces [29] and thought to be a substantial advantage of optogenetics over the electrical stimulation and recording.…”

mentioning

confidence: 99%