Dynamic illumination of spatially restricted or large brain volumes via a single tapered optical fiber DOI
Ferruccio Pisanello,

Gil Mandelbaum,

Marco Pisanello

et al.

Nature Neuroscience, Journal Year: 2017, Volume and Issue: 20(8), P. 1180 - 1188

Published: June 19, 2017

Language: Английский

Ultrafast neuronal imaging of dopamine dynamics with designed genetically encoded sensors DOI Open Access
Tommaso Patriarchi, Jounhong Ryan Cho, Katharina Merten

et al.

Science, Journal Year: 2018, Volume and Issue: 360(6396)

Published: May 31, 2018

Imaging dopamine release in the brain Neuromodulator alters function of target circuits poorly known ways. An essential step to address this knowledge gap is measure dynamics neuromodulatory signals while simultaneously manipulating elements circuit during behavior. Patriarchi et al. developed fluorescent protein–based indicators visualize spatial and temporal directly with high fidelity resolution. In cortex, two-photon imaging these was used map activity at cellular Science , issue p. eaat4422

Language: Английский

Citations

987

Computational psychiatry as a bridge from neuroscience to clinical applications DOI
Quentin J. M. Huys, Tiago V. Maia, Michael J. Frank

et al.

Nature Neuroscience, Journal Year: 2016, Volume and Issue: 19(3), P. 404 - 413

Published: Feb. 23, 2016

Language: Английский

Citations

921

Striatal circuits for reward learning and decision-making DOI
Julia Cox, Ilana B. Witten

Nature reviews. Neuroscience, Journal Year: 2019, Volume and Issue: 20(8), P. 482 - 494

Published: June 6, 2019

Language: Английский

Citations

493

A high-resolution probabilistic in vivo atlas of human subcortical brain nuclei DOI Creative Commons
Wolfgang M. Pauli, Amanda Nili, J. Michael Tyszka

et al.

Scientific Data, Journal Year: 2018, Volume and Issue: 5(1)

Published: April 17, 2018

Abstract Recent advances in magnetic resonance imaging methods, including data acquisition, pre-processing and analysis, have benefited research on the contributions of subcortical brain nuclei to human cognition behavior. At same time, these developments led an increasing need for a high-resolution probabilistic vivo anatomical atlas nuclei. In order address this need, we constructed high spatial resolution, three-dimensional templates, using high-accuracy diffeomorphic registration T 1 - 2 weighted structural images from 168 typical adults between 22 35 years old. many tissue boundaries are clearly visible, which would otherwise be impossible delineate individual studies. The resulting delineations complement current histology-based atlases. We further created companion library software tools development, offer open evolving resource creation crowd-sourced brain.

Language: Английский

Citations

452

The Role of Variability in Motor Learning DOI Open Access
Ashesh K. Dhawale, Maurice A. Smith, Bence P. Ölveczky

et al.

Annual Review of Neuroscience, Journal Year: 2017, Volume and Issue: 40(1), P. 479 - 498

Published: May 10, 2017

Trial-to-trial variability in the execution of movements and motor skills is ubiquitous widely considered to be unwanted consequence a noisy nervous system. However, recent studies have suggested that may also feature how sensorimotor systems operate learn. This view, rooted reinforcement learning theory, equates with purposeful exploration space that, when coupled reinforcement, can drive learning. Here we review explore relationship between both humans animal models. We discuss neural circuit mechanisms underlie generation regulation consider implications this work has for our understanding

Language: Английский

Citations

443

Dopamine and Cognitive Control in Prefrontal Cortex DOI
Torben Ott, Andreas Nieder

Trends in Cognitive Sciences, Journal Year: 2019, Volume and Issue: 23(3), P. 213 - 234

Published: Jan. 31, 2019

Language: Английский

Citations

442

Neural Circuitry of Reward Prediction Error DOI
Mitsuko Watabe‐Uchida, Neir Eshel, Naoshige Uchida

et al.

Annual Review of Neuroscience, Journal Year: 2017, Volume and Issue: 40(1), P. 373 - 394

Published: April 25, 2017

Dopamine neurons facilitate learning by calculating reward prediction error, or the difference between expected and actual reward. Despite two decades of research, it remains unclear how dopamine make this calculation. Here we review studies that tackle problem from a diverse set approaches, anatomy to electrophysiology computational modeling behavior. Several patterns emerge synthesis: themselves calculate rather than inherit passively upstream regions; they combine multiple separate redundant inputs, which are interconnected in dense recurrent network; despite complexity output is remarkably homogeneous robust. The more study simple arithmetic computation, knottier appears be, suggesting daunting (but stimulating) path ahead for neuroscience generally.

Language: Английский

Citations

408

A distributional code for value in dopamine-based reinforcement learning DOI
Will Dabney, Zeb Kurth‐Nelson, Naoshige Uchida

et al.

Nature, Journal Year: 2020, Volume and Issue: 577(7792), P. 671 - 675

Published: Jan. 15, 2020

Language: Английский

Citations

390

Dopamine neurons create Pavlovian conditioned stimuli with circuit-defined motivational properties DOI
Benjamin T. Saunders, Jocelyn M. Richard, Elyssa B. Margolis

et al.

Nature Neuroscience, Journal Year: 2018, Volume and Issue: 21(8), P. 1072 - 1083

Published: July 19, 2018

Language: Английский

Citations

387

Dopamine neurons projecting to the posterior striatum reinforce avoidance of threatening stimuli DOI
William Menegas, Korleki Akiti, Ryunosuke Amo

et al.

Nature Neuroscience, Journal Year: 2018, Volume and Issue: 21(10), P. 1421 - 1430

Published: Aug. 21, 2018

Language: Английский

Citations

346