Imprinting and recalling cortical ensembles

Carrillo-Reid, Luis; Yang, Wankou; Bandô, Yoshio; Peterka, Darcy S.; Yuste, Rafael

doi:10.1126/science.aaf7560

Cited by 260 publications

(370 citation statements)

References 39 publications

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“…Another application emerged with (i) the discovery of high responsivity of red light–driven opsins to two-photon illumination, enabling single-cell resolution optogenetics in brain tissue (63), and (ii) integration of red light–excited control with blue light–excited readout (via genetically encoded activity sensors such as GCaMP Ca 2+ reporters). Enabling these in vivo all-optical play-in/read-out experiments (50, 75–78) has opened the door to tuning optogenetic control in order to match timing and amplitude of naturally occurring activity in the same circuit elements (3, 76), and more broadly to keeping stimulation attuned to native dynamics and events in real time through closed-loop and activity-guided strategies (50, 74–78). Many opsins are now available for redshifted excitation, including not just VChR1 and C1V1 but also the VChR1-based ReaChR (79) as well as MChR1 (80), Chrimson (65), and bReaCHES (77) (with ChETA modifications for speed).…”

Section: Spectral Propertiesmentioning

confidence: 99%

The form and function of channelrhodopsin

Deisseroth

Hegemann

2017

Science

222

214

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Channelrhodopsins are light-gated ion channels that, via regulation of flagellar function, enable single-celled motile algae to seek ambient light conditions suitable for photosynthesis and survival. These plant behavioral responses were initially investigated more than 150 years ago. Recently, major principles of function for light-gated ion channels have been elucidated by creating channelrhodopsins with kinetics that are accelerated or slowed over orders of magnitude, by discovering and designing channelrhodopsins with altered spectral properties, by solving the high-resolution channelrhodopsin crystal structure, and by structural model–guided redesign of channelrhodopsins for altered ion selectivity. Each of these discoveries not only revealed basic principles governing the operation of light-gated ion channels, but also enabled the creation of new proteins for illuminating, via optogenetics, the fundamentals of brain function.

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Section: Spectral Propertiesmentioning

confidence: 99%

The form and function of channelrhodopsin

Deisseroth

Hegemann

2017

Science

222

214

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“…8D, see also Supplemental Information). When combined with light-sensitive optogenetic actuators, patterned illumination can perturb electrical activity with near cellular resolution (Baker et al, 2016; Carrillo-Reid et al, 2016; Packer et al, 2015; Papagiakoumou et al, 2010; Rickgauer et al, 2014). …”

Section: Considerations Of Interventional Experimental Designmentioning

confidence: 99%

Cracking the Neural Code for Sensory Perception by Combining Statistics, Intervention, and Behavior

Panzeri

Harvey

Piasini

et al. 2017

Neuron

199

202

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Summary The two basic processes underlying perceptual decisions – how neural responses encode stimuli, and how they inform behavioral choices – have mainly been studied separately. Thus, although many spatiotemporal features of neural population activity, or “neural codes,” have been shown to carry sensory information, it is often unknown whether the brain uses these features for perception. To address this issue, we propose a new framework centered on redefining the neural code as the neural features that carry sensory information used by the animal to drive appropriate behavior; that is, the features that have an intersection between sensory and choice information. We show how this framework leads to a new statistical analysis of neural activity recorded during behavior that can identify such neural codes, and we discuss how to combine intersection-based analysis of neural recordings with intervention on neural activity to determine definitively whether specific neural activity features are involved in a task.

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“…Later, if these patterns or their noisy versions are used to provoke the network, it settles on the original patterns after several rounds of activation updates on the recurrent weights (recall), thus stored patterns act as attractors. It is of high importance that the existence of such networks has been experimentally validated in the visual cortex of awake mice by optogenetic methods 36 . Some versions of the learning rule allow for iterative learning without catastrophic forgetting and enable palimpsest memory.…”

Section: Introductionmentioning

confidence: 99%

Breeding novel solutions in the brain: A model of Darwinian neurodynamics

et al. 2017

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The fact that surplus connections and neurons are pruned during Background development is well established. We complement this selectionist picture by a proof-of-principle model of evolutionary search in the brain, that accounts for new variations in theory space. We present a model for Darwinian evolutionary search for candidate solutions in the brain.: We combine known components of the brain -recurrent neural Methods networks (acting as attractors), the action selection loop and implicit working memory -to provide the appropriate Darwinian architecture. We employ a population of attractor networks with palimpsest memory. The action selection loop is employed with winners-share-all dynamics to select for candidate solutions that are transiently stored in implicit working memory.: We document two processes: selection of stored solutions and Results evolutionary search for novel solutions. During the replication of candidate solutions attractor networks occasionally produce recombinant patterns, increasing variation on which selection can act. Combinatorial search acts on multiplying units (activity patterns) with hereditary variation and novel variants appear due to (i) noisy recall of patterns from the attractor networks, (ii) noise during transmission of candidate solutions as messages between networks, and, (iii) spontaneously generated, untrained patterns in spurious attractors.: Attractor dynamics of recurrent neural networks can be used to Conclusions model Darwinian search. The proposed architecture can be used for fast search among stored solutions (by selection) and for evolutionary search when novel candidate solutions are generated in successive iterations. Since all the suggested components are present in advanced nervous systems, we hypothesize that the brain could implement a truly evolutionary combinatorial search system, capable of generating novel variants. Keywords

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Imprinting and recalling cortical ensembles

Cited by 260 publications

References 39 publications

The form and function of channelrhodopsin

The form and function of channelrhodopsin

Cracking the Neural Code for Sensory Perception by Combining Statistics, Intervention, and Behavior

Breeding novel solutions in the brain: A model of Darwinian neurodynamics

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