Single-trial neural dynamics are dominated by richly varied movements

Nature Neuroscience, Journal Year: 2019, Volume and Issue: 22(10), P. 1677 - 1686

Published: Sept. 24, 2019

Language: Английский

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Neuropixels 2.0: A miniaturized high-density probe for stable, long-term brain recordings

Science, Journal Year: 2021, Volume and Issue: 372(6539)

Published: April 15, 2021

Measuring the dynamics of neural processing across time scales requires following spiking thousands individual neurons over milliseconds and months. To address this need, we introduce Neuropixels 2.0 probe together with newly designed analysis algorithms. The has more than 5000 sites is miniaturized to facilitate chronic implants in small mammals recording during unrestrained behavior. High-quality recordings long were reliably obtained mice rats six laboratories. Improved site density arrangement combined created data methods enable automatic post hoc correction for brain movements, allowing from same 2 These probes algorithms stable free behavior, even animals such as mice.

Language: Английский

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Distributed coding of choice, action and engagement across the mouse brain

Nature, Journal Year: 2019, Volume and Issue: 576(7786), P. 266 - 273

Published: Nov. 27, 2019

Language: Английский

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Computation Through Neural Population Dynamics

Annual Review of Neuroscience, Journal Year: 2020, Volume and Issue: 43(1), P. 249 - 275

Published: July 8, 2020

Significant experimental, computational, and theoretical work has identified rich structure within the coordinated activity of interconnected neural populations. An emerging challenge now is to uncover nature associated computations, how they are implemented, what role play in driving behavior. We term this computation through population dynamics. If successful, framework will reveal general motifs quantitatively describe dynamics implement computations necessary for goal-directed Here, we start with a mathematical primer on dynamical systems theory analytical tools apply perspective experimental data. Next, highlight some recent discoveries resulting from successful application systems. focus studies spanning motor control, timing, decision-making, working memory. Finally, briefly discuss promising lines investigation future directions framework.

Language: Английский

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High-dimensional geometry of population responses in visual cortex

Nature, Journal Year: 2019, Volume and Issue: 571(7765), P. 361 - 365

Published: June 26, 2019

Language: Английский

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Survey of spiking in the mouse visual system reveals functional hierarchy

Nature, Journal Year: 2021, Volume and Issue: 592(7852), P. 86 - 92

Published: Jan. 20, 2021

Language: Английский

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Computational Neuroethology: A Call to Action

Neuron, Journal Year: 2019, Volume and Issue: 104(1), P. 11 - 24

Published: Oct. 1, 2019

Language: Английский

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Deep learning tools for the measurement of animal behavior in neuroscience

Current Opinion in Neurobiology, Journal Year: 2019, Volume and Issue: 60, P. 1 - 11

Published: Nov. 29, 2019

Language: Английский

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Physical reservoir computing—an introductory perspective

Japanese Journal of Applied Physics, Journal Year: 2020, Volume and Issue: 59(6), P. 060501 - 060501

Published: April 27, 2020

Understanding the fundamental relationships between physics and its information-processing capability has been an active research topic for many years. Physical reservoir computing is a recently introduced framework that allows one to exploit complex dynamics of physical systems as devices. This particularly suited edge devices, in which information processing incorporated at (e.g., into sensors) decentralized manner reduce adaptation delay caused by data transmission overhead. paper aims illustrate potentials using examples from soft robotics provide concise overview focusing on basic motivations introducing it, stem number fields, including machine learning, nonlinear dynamical systems, biological science, materials physics.

Language: Английский

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A connectome of the Drosophila central complex reveals network motifs suitable for flexible navigation and context-dependent action selection

eLife, Journal Year: 2021, Volume and Issue: 10

Published: Oct. 26, 2021

Flexible behaviors over long timescales are thought to engage recurrent neural networks in deep brain regions, which experimentally challenging study. In insects, circuit dynamics a region called the central complex (CX) enable directed locomotion, sleep, and context- experience-dependent spatial navigation. We describe first complete electron microscopy-based connectome of

Language: Английский

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