Ramp-to-threshold dynamics in a hindbrain population controls the timing of spontaneous saccades

Ramirez, Alexandro D.; Aksay, Emre

doi:10.1038/s41467-021-24336-w

Cited by 22 publications

(29 citation statements)

References 72 publications

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“…Subpopulations of cells in the aHB are known to represent eye-related variables such as eye position and saccade timing (Wolf et al, 2017; Ramirez and Aksay, 2021). We therefore decided to understand whether eye motion could also modulate the phase of the network.…”

Section: Resultsmentioning

confidence: 99%

Neural dynamics and architecture of the heading direction circuit in a vertebrate brain

Petrucco

Lavian

et al. 2022

Preprint

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Animals can use different strategies to navigate. They may guide their movements by relying on external cues in their environment or, alternatively, by using an internal cognitive map of the space around them and their position within it. An essential part of this representation are heading cells, neurons whose activity depends on the heading direction of the animal. Although those cells have been found in vertebrates, the full network has never been observed and there is very little mechanistic understanding of how these cells acquire their response properties. In this study, we use volumetric functional imaging in larval zebrafish to observe, for the first time in a vertebrate, a full network that encodes allocentric heading direction. This network of approximately one hundred inhibitory neurons is arranged in an anatomical circle in the anterior hindbrain. Its activity is driven purely by the integration of internally generated signals, indicating that a simple vertebrate brain can encode maps of how an animal moves within its surroundings. Single cell reconstructions of electron micrographs allow us to uncover how the connectivity pattern of neurons within the network supports the implementation of a ring attractor network. The neurons we identify share features with neurons in the dorsal tegmentum nucleus of rodents and the fly central complex, showing that similar connectivity and mechanistic principles underlie the generation of cognitive maps of heading direction across the animal kingdom.

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Section: Resultsmentioning

confidence: 99%

Neural dynamics and architecture of the heading direction circuit in a vertebrate brain

Petrucco

Lavian

et al. 2022

Preprint

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“…We resorted to comparison with other animals because our calcium imaging of the neurons in the EM volume (Vishwanathan et al, 2017) had highly incomplete coverage due to technical limitations. Recordings were obtained while the animals performed spontaneous eye movements in the dark, with activity ranging from neurons that exhibited bursts during saccades to those with perfectly persistent firing during fixations (Ramirez and Aksay, 2018). The images from 20 age-matched animals were combined by registering them to a reference atlas (Randlett et al, 2015).…”

Section: Resultsmentioning

confidence: 99%

“…The complete methods for recording calcium activity used to create the functional maps are reported in (Ramirez and Aksay, 2018). Briefly, we used two-photon, raster-scanning microscopy to image calcium activity from single neurons throughout the hindbrain of 7-8 day old transgenic larvae expressing nuclear-localized GCaMP6f, Tg(HuC:GCaMP6f-H2B) strain cy73-431 from Misha Ahrens’ lab.…”

Section: Methodsmentioning

confidence: 99%

Predicting modular functions and neural coding of behavior from a synaptic wiring diagram

Vishwanathan

Ramirez

et al. 2020

Preprint

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Neuronal wiring diagrams reconstructed from electron microscopic images are enabling new ways of attacking neuroscience questions. We address two central issues, modularity and neural coding, by reconstructing and analyzing a wiring diagram from a larval zebrafish brainstem. We identified a recurrently connected "center" within the 3000-node graph, and applied graph clustering algorithms to divide the center into two modules with stronger connectivity within than between modules. Outgoing connection patterns and registration to maps of neural activity suggested the modules were specialized for body and eye movements. The eye movement module further subdivided into two submodules corresponding to the control of the two eyes. We constructed a recurrent network model of the eye movement module with connection strengths estimated from synapse numbers. Neural activity in the model replicated the statistics of eye position encoding across multiple populations of neurons as observed by calcium imaging. Our findings show that synapse-level wiring diagrams can be used to extract structural modules with interpretable functions in the vertebrate brain, and can be related to the encoding of computational variables important for behavior. We also show through a potential synapse formalism that these modeling successes require true synaptic connectivity; connectivity inferred from arbor overlap is insufficient.

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“…Here we introduced a data-driven network model, whose biologically-grounded architecture and relative simplicity make it both quantitatively accurate and amenable to detailed mathematical analysis. We implemented this approach on functional recordings performed at various temperature of a key population of neurons in the zebrafish larvae brain, called ARTR, that drives the orientation of tail bouts and gaze (Dunn et al, 2016; Wolf et al, 2017; Ramirez & Aksay, 2021; Leyden et al, 2021).…”

Section: Discussionmentioning

confidence: 99%

“…It is therefore important to develop quantitative, yet interpretable approaches to tackle the functions carried out by large neural populations. The present work is an attempt to do so in the specific context of the anterior rhombencephalic turning region (ARTR), a circuit in the zebrafish larva that shows slow (∼ 10 sec) endogenous alternations between left and right active states driving the gaze orientation and chaining of leftward/rightward swim bouts (Ahrens et al, 2013; Dunn et al, 2016; Wolf et al, 2017; Ramirez & Aksay, 2021; Leyden et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Emergence of time persistence in a data-driven neural network model

Wolf¹,

Goc

Cocco

et al. 2022

Preprint

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Establishing accurate as well as interpretable models of networks activity is an open challenge in systems neuroscience. Here we infer an energy-based model of the ARTR, a circuit that controls zebrafish swimming statistics, using functional recordings of the spontaneous activity of hundreds of neurons. Although our model is trained to reproduce the low-order statistics of the network activity at short time-scales, its simulated dynamics quantitatively captures the slowly alternating activity of the ARTR. It further reproduces the modulation of this persistent dynamics by the bath temperature and visual stimulation. Mathematical analysis of the model unveils a low-dimensional landscape-based representation of the ARTR activity, where the slow network dynamics reflects Arrhenius-like barriers crossings between metastable states. Our work thus shows how data-driven models built from large neural populations recordings can be reduced to low-dimensional functional models in order to reveal the fundamental mechanisms controlling the collective neuronal dynamics.

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Ramp-to-threshold dynamics in a hindbrain population controls the timing of spontaneous saccades

Cited by 22 publications

References 72 publications

Neural dynamics and architecture of the heading direction circuit in a vertebrate brain

Neural dynamics and architecture of the heading direction circuit in a vertebrate brain

Predicting modular functions and neural coding of behavior from a synaptic wiring diagram

Emergence of time persistence in a data-driven neural network model

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