Optogenetic feedback control of neural activity

Newman, Jonathan P.; Fong, Ming‐fai; Millard, Daniel C.; Whitmire, Clarissa J.; Stanley, Garrett B.; Potter, Steve M.

doi:10.7554/elife.07192

Cited by 118 publications

(107 citation statements)

References 55 publications

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“…Similar to the roles of specific cell-types in the enhancement of SSA in cortex, the ability of cortical feedback to modulate information transmission presents a complementary role for modulatory feedback in rapid sensory encoding. Disentangling the role of any given neuron in inducing or demonstrating sensory adaptation will likely require a more sophisticated understanding of artificial stimulation techniques (Millard et al, 2015) that can be implemented in conjunction with cell-type specificity and real-time feedback control of neural activity to functionally decouple causally related variables (Grosenick et al, 2015; Newman et al, 2015). By understanding the part each neural component plays in building the network level response, we can begin to understand the functional role of the circuitry in dynamic encoding.…”

Section: Implications Of Highly Interconnected Circuitry In Adaptive mentioning

confidence: 99%

Rapid Sensory Adaptation Redux: A Circuit Perspective

Whitmire

Stanley

2016

Neuron

123

116

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Summary Adaptation is fundamental to life. All organisms adapt over timescales that span from evolution to generations and lifetimes to moment-by-moment interactions. The nervous system is particularly adept at rapidly adapting to change, and this in fact may be one of its fundamental principles of organization and function. Rapid forms of sensory adaptation have been well-documented across all sensory modalities in a wide range of organisms, yet we do not have a comprehensive understanding of the adaptive cellular mechanisms that ultimately give rise to the corresponding percepts due in part to the complexity of the circuitry. In this Perspective, we aim to build links between adaptation at multiple scales of neural circuitry by investigating the differential adaptation across brain regions and sub-regions and across specific cell-types, for which the explosion of modern tools has just begun to enable. This investigation points to a set of challenges for the field to link functional observations to adaptive properties of the neural circuit that ultimately underlie percepts.

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Section: Implications Of Highly Interconnected Circuitry In Adaptive mentioning

confidence: 99%

Rapid Sensory Adaptation Redux: A Circuit Perspective

Whitmire

Stanley

2016

Neuron

123

116

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“…The masking stimulus was 618 provided by two 465 nm wavelength LEDs mounted on top of the computer screens facing 619 the animal (Thorlabs LED465E, Thorlabs, NJ, USA). Optogenetic stimulation light was 620 provided by a 470 nm fiber coupled LED (Thorlabs M470F3) powered by a Cyclops LED 621 driver (Newman et al, 2015). Stimulation consisted of a solid light pulse with a maximum 622 duration of 10 seconds (Lewis et al, 2015).…”

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confidence: 99%

Representation of Visual Landmarks in Retrosplenial Cortex

Fischer

Soto-Albors

Buck

et al. 2019

Preprint

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8The process by which visual information is incorporated into the brain's spatial framework 9to represent landmarks is poorly understood. Studies in humans and rodents suggest that 10 retrosplenial cortex (RSC) plays a key role in these computations. We developed an RSC-11 dependent behavioral task in which head-fixed mice learned the spatial relationship 12 between visual landmark cues and hidden reward locations. Two-photon imaging 13revealed that these cues served as dominant reference points for most task-active 14neurons and anchored the spatial code in RSC. Presenting the same environment but 15 decoupled from mouse behavior degraded encoding fidelity. Analyzing visual and motor 16responses showed that landmark codes were the result of supralinear integration. 17Surprisingly, V1 axons recorded in RSC showed similar receptive fields. However, they 18 were less modulated by task engagement, indicating that landmark representations in 19RSC are the result of local computations. Our data provide cellular-and network-level 20insight into how RSC represents landmarks. 21 22

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“…Although closed-loop feedback has previously been used to optimize both optical and electrical 432 stimulation, its use has been more focused on real-time instantaneous feedback control, rather than stimulus optimization (Wagenaar, 2005;Wallach et al, 2011;Newman et al, 2013Newman et al, , 2015. Moving 434 beyond sensory characterization, closed-loop feedback has also been shown to improve brain-computer interfaces (Cunningham et al, 2011;Shanechi et al, 2016), to induce motor plasticity (Jackson et al, 436 2006), and to provide all-optical control of neural circuits (Zhang et al, 2018).…”

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confidence: 99%

Optimizing optogenetic stimulation protocols in auditory corticofugal neurons based on closed-loop spike feedback

Vila

Williamson

Hancock

et al. 2018

Preprint

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2Optogenetics provides a means to probe functional connections between brain areas. By activating a set of presynaptic neurons and recording the activity from a downstream brain area, one 4 can establish the sign and strength of a feedforward connection. One challenge is that there are virtually limitless patterns that can be used to stimulate a presynaptic brain area. Functional influences on 6 downstream brain areas can depend not just on whether presynaptic neurons were activated, but how they were activated. Corticofugal axons from the auditory cortex (ACtx) heavily innervate the auditory 8 tectum, the inferior colliculus (IC). Despite the anatomical weight of this connection, optogenetic activation of ACtx neurons produced only modest changes in the IC neuron firing rates. To determine 30 activation patterns associated with the strongest effects on IC firing rates, we applied a machine learning algorithm that utilized the firing rate of single IC neurons to iteratively tailor the voltage 32 command signal sent to the laser. We show that the temporal patterning of ACtx spiking strongly impacts the cortical influence on midbrain sound processing. 34 145:209-223. Bleeck S, Patterson RD, Winter IM (2003) Using genetic algorithms to find the most effective stimulus for 458 sensory neurons. J Neurosci Methods 125:73-82. Chambers AR, Hancock KE, Maison SF, Liberman MC, Polley DB (2012) Sound-evoked olivocochlear 460 activation in unanesthetized mice. J Assoc Res Otolaryngol 13:209-217. Chambers AR, Hancock KE, Sen K, Polley DB (2014) Online stimulus optimization rapidly reveals 462 multidimensional selectivity in auditory cortical neurons. J Neurosci 34:8963-8975. Chen C, Cheng M, Ito T, Song S (2018) Neuronal Organization in the Inferior Colliculus Revisited with 464 Cell-Type-Dependent Monosynaptic Tracing. J Neurosci 38:3318-3332. Coomes DL, Schofield RM, Schofield BR (2005) Unilateral and bilateral projections from cortical cells to 466 the inferior colliculus in guinea pigs. Brain Res 1042:62-72. Cunningham JP, Nuyujukian P, Gilja V, Chestek CA, Ryu SI, Shenoy K V. (2011) A closed-loop human 468 simulator for investigating the role of feedback control in brain-machine interfaces. J Neurophysiol 105:1932-1949. 470 Diamond IT, Jones EG, Powell TPS (1969) The projection of the auditory cortex upon the diencephalon and brain stem in the cat. Brain Res 15:305-340.472 DiMattina C, Zhang K (2013) Adaptive stimulus optimization for sensory systems neuroscience. Front Neural Circuits 7:1-16. 474 Feliciano M, Potashner SJ (1995) Evidence for a Glutamatergic Pathway from the Guinea Pig Auditory Cortex to the Inferior Colliculus. J Neurochem 65:1348-1357. 476 Feng X-J, Shea-Brown E, Greenwald B, Kosut R, Rabitz H (2007a) Optimal deep brain stimulation of the subthalamic nucleus-a computational study. J Comput Neurosci. 478 Feng XJ, Greenwald B, Rabitz H, Shea-Brown E, Kosut R (2007b) Toward closed-loop optimization of deep brain stimulation for Parkinson's disease: Concepts and lessons from a computational model. J 480 Ne...

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Optogenetic feedback control of neural activity

Cited by 118 publications

References 55 publications

Rapid Sensory Adaptation Redux: A Circuit Perspective

Rapid Sensory Adaptation Redux: A Circuit Perspective

Representation of Visual Landmarks in Retrosplenial Cortex

Optimizing optogenetic stimulation protocols in auditory corticofugal neurons based on closed-loop spike feedback

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