Literature DB >> 24728268

Volitional modulation of optically recorded calcium signals during neuroprosthetic learning.

Kelly B Clancy1, Aaron C Koralek2, Rui M Costa3, Daniel E Feldman2,4, Jose M Carmena2,5,6.   

Abstract

Brain-machine interfaces are not only promising for neurological applications, but also powerful for investigating neuronal ensemble dynamics during learning. We trained mice to operantly control an auditory cursor using spike-related calcium signals recorded with two-photon imaging in motor and somatosensory cortex. Mice rapidly learned to modulate activity in layer 2/3 neurons, evident both across and within sessions. Learning was accompanied by modifications of firing correlations in spatially localized networks at fine scales.

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Year:  2014        PMID: 24728268      PMCID: PMC4361947          DOI: 10.1038/nn.3712

Source DB:  PubMed          Journal:  Nat Neurosci        ISSN: 1097-6256            Impact factor:   24.884


  23 in total

1.  Actions from thoughts.

Authors:  M A Nicolelis
Journal:  Nature       Date:  2001-01-18       Impact factor: 49.962

2.  Functional biases in visual cortex neurons with identified projections to higher cortical targets.

Authors:  Beata Jarosiewicz; James Schummers; Wasim Q Malik; Emery N Brown; Mriganka Sur
Journal:  Curr Biol       Date:  2012-02-02       Impact factor: 10.834

Review 3.  How silent is the brain: is there a "dark matter" problem in neuroscience?

Authors:  Shy Shoham; Daniel H O'Connor; Ronen Segev
Journal:  J Comp Physiol A Neuroethol Sens Neural Behav Physiol       Date:  2006-03-21       Impact factor: 1.836

4.  Efficient subpixel image registration algorithms.

Authors:  Manuel Guizar-Sicairos; Samuel T Thurman; James R Fienup
Journal:  Opt Lett       Date:  2008-01-15       Impact factor: 3.776

5.  Chronic stress causes frontostriatal reorganization and affects decision-making.

Authors:  Eduardo Dias-Ferreira; João C Sousa; Irene Melo; Pedro Morgado; Ana R Mesquita; João J Cerqueira; Rui M Costa; Nuno Sousa
Journal:  Science       Date:  2009-07-31       Impact factor: 47.728

6.  Learning-related fine-scale specificity imaged in motor cortex circuits of behaving mice.

Authors:  Takaki Komiyama; Takashi R Sato; Daniel H O'Connor; Ying-Xin Zhang; Daniel Huber; Bryan M Hooks; Mariano Gabitto; Karel Svoboda
Journal:  Nature       Date:  2010-04-07       Impact factor: 49.962

7.  Inducing γ oscillations and precise spike synchrony by operant conditioning via brain-machine interface.

Authors:  Ben Engelhard; Nofar Ozeri; Zvi Israel; Hagai Bergman; Eilon Vaadia
Journal:  Neuron       Date:  2013-01-23       Impact factor: 17.173

8.  Corticostriatal plasticity is necessary for learning intentional neuroprosthetic skills.

Authors:  Aaron C Koralek; Xin Jin; John D Long; Rui M Costa; Jose M Carmena
Journal:  Nature       Date:  2012-03-04       Impact factor: 49.962

9.  Reach and grasp by people with tetraplegia using a neurally controlled robotic arm.

Authors:  Leigh R Hochberg; Daniel Bacher; Beata Jarosiewicz; Nicolas Y Masse; John D Simeral; Joern Vogel; Sami Haddadin; Jie Liu; Sydney S Cash; Patrick van der Smagt; John P Donoghue
Journal:  Nature       Date:  2012-05-16       Impact factor: 49.962

10.  Ultrasensitive fluorescent proteins for imaging neuronal activity.

Authors:  Tsai-Wen Chen; Trevor J Wardill; Yi Sun; Stefan R Pulver; Sabine L Renninger; Amy Baohan; Eric R Schreiter; Rex A Kerr; Michael B Orger; Vivek Jayaraman; Loren L Looger; Karel Svoboda; Douglas S Kim
Journal:  Nature       Date:  2013-07-18       Impact factor: 49.962

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  49 in total

1.  A rodent brain-machine interface paradigm to study the impact of paraplegia on BMI performance.

Authors:  Nathaniel R Bridges; Michael Meyers; Jonathan Garcia; Patricia A Shewokis; Karen A Moxon
Journal:  J Neurosci Methods       Date:  2018-05-31       Impact factor: 2.390

2.  Structure of a single whisker representation in layer 2 of mouse somatosensory cortex.

Authors:  Kelly B Clancy; Philipp Schnepel; Antara T Rao; Daniel E Feldman
Journal:  J Neurosci       Date:  2015-03-04       Impact factor: 6.167

Review 3.  Physiological properties of brain-machine interface input signals.

Authors:  Marc W Slutzky; Robert D Flint
Journal:  J Neurophysiol       Date:  2017-06-14       Impact factor: 2.714

Review 4.  Closed-loop brain training: the science of neurofeedback.

Authors:  Ranganatha Sitaram; Tomas Ros; Luke Stoeckel; Sven Haller; Frank Scharnowski; Jarrod Lewis-Peacock; Nikolaus Weiskopf; Maria Laura Blefari; Mohit Rana; Ethan Oblak; Niels Birbaumer; James Sulzer
Journal:  Nat Rev Neurosci       Date:  2016-12-22       Impact factor: 34.870

5.  Shedding light on learning.

Authors:  Byron M Yu; Steven M Chase
Journal:  Nat Neurosci       Date:  2014-06       Impact factor: 24.884

Review 6.  Brain-computer interfaces for communication and rehabilitation.

Authors:  Ujwal Chaudhary; Niels Birbaumer; Ander Ramos-Murguialday
Journal:  Nat Rev Neurol       Date:  2016-08-19       Impact factor: 42.937

Review 7.  Parsing learning in networks using brain-machine interfaces.

Authors:  Amy L Orsborn; Bijan Pesaran
Journal:  Curr Opin Neurobiol       Date:  2017-08-24       Impact factor: 6.627

Review 8.  Neuroplasticity subserving the operation of brain-machine interfaces.

Authors:  Karim G Oweiss; Islam S Badreldin
Journal:  Neurobiol Dis       Date:  2015-05-09       Impact factor: 5.996

9.  An open source, wireless capable miniature microscope system.

Authors:  William A Liberti; L Nathan Perkins; Daniel P Leman; Timothy J Gardner
Journal:  J Neural Eng       Date:  2017-08       Impact factor: 5.379

Review 10.  Brain-computer interfaces for dissecting cognitive processes underlying sensorimotor control.

Authors:  Matthew D Golub; Steven M Chase; Aaron P Batista; Byron M Yu
Journal:  Curr Opin Neurobiol       Date:  2016-01-19       Impact factor: 6.627

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