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Bence P. Olveczky

Affiliations: 
Organismic and Evolutionary Biology Harvard University, Cambridge, MA, United States 
Area:
vocal learning in the songbird, Motor sequence learning in rodents
Website:
http://www.fas.harvard.edu/~biophys/Bence_P_Olveczky.htm
Google:
"Bence Olveczky"
Bio:

http://www.oeb.harvard.edu/faculty/olveczky/index.html

Mean distance: 13.32 (cluster 6)
 
SNBCP
Cross-listing: Chemistry Tree

Parents

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Markus Meister grad student 2003 Harvard
 (Retinal processing of natural motion.)
Michale S. Fee post-doc MIT

Children

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Timothy Markman research assistant Harvard
Valentin André Normand research assistant Harvard
Chong Guo research assistant 2010-2012 Harvard
Farhan Ali grad student Harvard
Risa Kawai grad student 2009- Harvard
Jonathan Garst Orozco grad student 2009- Harvard
Rajesh Poddar grad student 2009- Harvard
Raymond Ko grad student 2010- Harvard
Alexandre Kempf grad student 2014-2014 Harvard
Adam Raymond Kampff post-doc Harvard
Steffen Wolff post-doc Harvard
Antoniu L. Fantana post-doc 2007- Harvard
Claude Wang post-doc 2010-
Jesse D. Marshall post-doc 2016- Harvard
Gerald Pho post-doc 2017- Harvard
Sharon M.H. Gobes post-doc 2009-2011 Harvard
Ashesh K. Dhawale post-doc 2012-2021 Harvard
Timothy Otchy research scientist 2008-2011 Harvard
BETA: Related publications

Publications

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Wolff SBE, Ko R, Ölveczky BP. (2022) Distinct roles for motor cortical and thalamic inputs to striatum during motor skill learning and execution. Science Advances. 8: eabk0231
Dhawale AK, Wolff SBE, Ko R, et al. (2021) The basal ganglia control the detailed kinematics of learned motor skills. Nature Neuroscience
Dunn TW, Marshall JD, Severson KS, et al. (2021) Geometric deep learning enables 3D kinematic profiling across species and environments. Nature Methods
Marshall JD, Aldarondo DE, Dunn TW, et al. (2020) Continuous Whole-Body 3D Kinematic Recordings across the Rodent Behavioral Repertoire. Neuron
Gershman SJ, Ölveczky BP. (2020) The neurobiology of deep reinforcement learning. Current Biology : Cb. 30: R629-R632
Williams AH, Poole B, Maheswaranathan N, et al. (2019) Discovering Precise Temporal Patterns in Large-Scale Neural Recordings through Robust and Interpretable Time Warping. Neuron
Dhawale AK, Miyamoto YR, Smith MA, et al. (2019) Adaptive Regulation of Motor Variability. Current Biology : Cb
Pehlevan C, Ali F, Ölveczky BP. (2018) Flexibility in motor timing constrains the topology and dynamics of pattern generator circuits. Nature Communications. 9: 977
Wolff SB, Ölveczky BP. (2018) The promise and perils of causal circuit manipulations. Current Opinion in Neurobiology. 49: 84-94
Dhawale AK, Poddar R, Wolff SB, et al. (2017) Automated long-term recording and analysis of neural activity in behaving animals. Elife. 6
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