Attractor and integrator networks in the brain DOI

Mikail Khona,

Ila Fiete

Nature reviews. Neuroscience, Journal Year: 2022, Volume and Issue: 23(12), P. 744 - 766

Published: Nov. 3, 2022

Language: Английский

Optogenetics: 10 years of microbial opsins in neuroscience DOI
Karl Deisseroth

Nature Neuroscience, Journal Year: 2015, Volume and Issue: 18(9), P. 1213 - 1225

Published: Aug. 26, 2015

Language: Английский

Citations

1169

Integration of optogenetics with complementary methodologies in systems neuroscience DOI
Christina K. Kim, Avishek Adhikari, Karl Deisseroth

et al.

Nature reviews. Neuroscience, Journal Year: 2017, Volume and Issue: 18(4), P. 222 - 235

Published: March 17, 2017

Language: Английский

Citations

648

Genetically encoded indicators of neuronal activity DOI
Michael Z. Lin, Mark J. Schnitzer

Nature Neuroscience, Journal Year: 2016, Volume and Issue: 19(9), P. 1142 - 1153

Published: Aug. 26, 2016

Language: Английский

Citations

620

Materials and technologies for soft implantable neuroprostheses DOI
Stéphanie P. Lacour, Grégoire Courtine, Jochen Guck

et al.

Nature Reviews Materials, Journal Year: 2016, Volume and Issue: 1(10)

Published: Sept. 27, 2016

Language: Английский

Citations

597

Novel electrode technologies for neural recordings DOI
Guosong Hong, Charles M. Lieber

Nature reviews. Neuroscience, Journal Year: 2019, Volume and Issue: 20(6), P. 330 - 345

Published: March 4, 2019

Language: Английский

Citations

585

Fast online deconvolution of calcium imaging data DOI Creative Commons
Johannes Friedrich, Pengcheng Zhou, Liam Paninski

et al.

PLoS Computational Biology, Journal Year: 2017, Volume and Issue: 13(3), P. e1005423 - e1005423

Published: March 14, 2017

Fluorescent calcium indicators are a popular means for observing the spiking activity of large neuronal populations, but extracting each neuron from raw fluorescence imaging data is nontrivial problem. We present fast online active set method to solve this sparse non-negative deconvolution Importantly, algorithm progresses through time series sequentially beginning end, thus enabling real-time estimation neural during session. Our generalization pool adjacent violators (PAVA) isotonic regression and inherits its linear-time computational complexity. gain remarkable increases in processing speed: more than one order magnitude compared currently employed state art convex solvers relying on interior point methods. Unlike these approaches, our can exploit warm starts; therefore optimizing model hyperparameters only requires handful passes data. A minor modification further improve quality inference by imposing constraint minimum spike size. The enables simultaneous $O(10^5)$ traces whole-brain larval zebrafish laptop.

Language: Английский

Citations

533

Thalamic Spindles Promote Memory Formation during Sleep through Triple Phase-Locking of Cortical, Thalamic, and Hippocampal Rhythms DOI Creative Commons
Charles-Francois V. Latchoumane, Hong‐Viet V. Ngo, Jan Born

et al.

Neuron, Journal Year: 2017, Volume and Issue: 95(2), P. 424 - 435.e6

Published: July 1, 2017

Language: Английский

Citations

508

Simultaneous fast measurement of circuit dynamics at multiple sites across the mammalian brain DOI
Christina K. Kim, Samuel Yang, Nandini Pichamoorthy

et al.

Nature Methods, Journal Year: 2016, Volume and Issue: 13(4), P. 325 - 328

Published: Feb. 15, 2016

Language: Английский

Citations

442

Disinhibition, a Circuit Mechanism for Associative Learning and Memory DOI Creative Commons
Johannes J. Letzkus, Steffen B. E. Wolff, Andreas Lüthi

et al.

Neuron, Journal Year: 2015, Volume and Issue: 88(2), P. 264 - 276

Published: Oct. 1, 2015

Language: Английский

Citations

395

Two’s company, three (or more) is a simplex DOI Creative Commons
Chad Giusti,

Robert Ghrist,

Danielle S. Bassett

et al.

Journal of Computational Neuroscience, Journal Year: 2016, Volume and Issue: 41(1), P. 1 - 14

Published: June 11, 2016

The language of graph theory, or network science, has proven to be an exceptional tool for addressing myriad problems in neuroscience. Yet, the use networks is predicated on a critical simplifying assumption: that quintessential unit interest brain dyad – two nodes (neurons regions) connected by edge. While rarely mentioned, this fundamental assumption inherently limits types neural structure and function graphs can used model. Here, we describe generalization overcomes these limitations, thereby offering broad range new possibilities terms modeling measuring phenomena. Specifically, explore simplicial complexes: developed field mathematics known as algebraic topology, increasing applicability real data due rapidly growing computational toolset. We review underlying mathematical formalism well budding literature applying complexes data, from electrophysiological recordings animal models hemodynamic fluctuations humans. Based flexibility tools recent ground-breaking insights into function, posit framework potential eclipse theory unraveling mysteries cognition.

Language: Английский

Citations

372