Attractor and integrator networks in the brain DOI

Mikail Khona,

Ila Fiete

Nature reviews. Neuroscience, Год журнала: 2022, Номер 23(12), С. 744 - 766

Опубликована: Ноя. 3, 2022

Язык: Английский

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

Nature Neuroscience, Год журнала: 2015, Номер 18(9), С. 1213 - 1225

Опубликована: Авг. 26, 2015

Язык: Английский

Процитировано

1169

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

и другие.

Nature reviews. Neuroscience, Год журнала: 2017, Номер 18(4), С. 222 - 235

Опубликована: Март 17, 2017

Язык: Английский

Процитировано

648

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

Nature Neuroscience, Год журнала: 2016, Номер 19(9), С. 1142 - 1153

Опубликована: Авг. 26, 2016

Язык: Английский

Процитировано

620

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

и другие.

Nature Reviews Materials, Год журнала: 2016, Номер 1(10)

Опубликована: Сен. 27, 2016

Язык: Английский

Процитировано

597

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

Nature reviews. Neuroscience, Год журнала: 2019, Номер 20(6), С. 330 - 345

Опубликована: Март 4, 2019

Язык: Английский

Процитировано

585

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

и другие.

PLoS Computational Biology, Год журнала: 2017, Номер 13(3), С. e1005423 - e1005423

Опубликована: Март 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.

Язык: Английский

Процитировано

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

и другие.

Neuron, Год журнала: 2017, Номер 95(2), С. 424 - 435.e6

Опубликована: Июль 1, 2017

Язык: Английский

Процитировано

508

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

и другие.

Nature Methods, Год журнала: 2016, Номер 13(4), С. 325 - 328

Опубликована: Фев. 15, 2016

Язык: Английский

Процитировано

442

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

и другие.

Neuron, Год журнала: 2015, Номер 88(2), С. 264 - 276

Опубликована: Окт. 1, 2015

Язык: Английский

Процитировано

395

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

Robert Ghrist,

Danielle S. Bassett

и другие.

Journal of Computational Neuroscience, Год журнала: 2016, Номер 41(1), С. 1 - 14

Опубликована: Июнь 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.

Язык: Английский

Процитировано

372