scholarly journals Expressions of Multiple Neuronal Dynamics during Sensorimotor Learning in the Motor Cortex of Behaving Monkeys

PLoS ONE ◽  
2011 ◽  
Vol 6 (7) ◽  
pp. e21626 ◽  
Author(s):  
Yael Mandelblat-Cerf ◽  
Itai Novick ◽  
Eilon Vaadia
2018 ◽  
Author(s):  
Chethan Pandarinath ◽  
K. Cora Ames ◽  
Abigail A Russo ◽  
Ali Farshchian ◽  
Lee E Miller ◽  
...  

In the fifty years since Evarts first recorded single neurons in motor cortex of behaving monkeys, great effort has been devoted to understanding their relation to movement. Yet these single neurons exist within a vast network, the nature of which has been largely inaccessible. With advances in recording technologies, algorithms, and computational power, the ability to study network-level phenomena is increasing exponentially. Recent experimental results suggest that the dynamical properties of these networks are critical to movement planning and execution. Here we discuss this dynamical systems perspective, and how it is reshaping our understanding of the motor cortices. Following an overview of key studies in motor cortex, we discuss techniques to uncover the “latent factors” underlying observed neural population activity. Finally, we discuss efforts to leverage these factors to improve the performance of brain-machine interfaces, promising to make these findings broadly relevant to neuroengineering as well as systems neuroscience.


Cell Reports ◽  
2018 ◽  
Vol 24 (8) ◽  
pp. 2191-2195.e4 ◽  
Author(s):  
Takahiro Kondo ◽  
Risa Saito ◽  
Masaki Otaka ◽  
Kimika Yoshino-Saito ◽  
Akihiro Yamanaka ◽  
...  

2017 ◽  
Author(s):  
Daniel R. Lametti ◽  
Harriet J. Smith ◽  
Phoebe Freidin ◽  
Kate E. Watkins

AbstractThe motor cortex and cerebellum are thought to be critical for learning and maintaining motor behaviours. Here we use tDCS to test the role of the motor cortex and cerebellum in sensorimotor learning in speech. During productions of ‘head’, ‘bed’, and ‘dead’, the first formant of the vowel sound was altered in real-time towards the first formant of the vowel sound in ‘had’, ‘bad’, and ‘dad’. Compensatory changes in first and second formant production were used as a measure of motor adaptation. TDCS to either the motor cortex or the cerebellum improved sensorimotor learning in speech compared to sham stimulation. However, in the case of cerebellar tDCS, production changes were restricted to the source of the acoustical error (i.e. the first formant). Motor cortex tDCS drove production changes that offset errors in the first formant, but, unlike cerebellar tDCS, adaptive changes in the second formant also occurred. The results suggest that motor cortex and cerebellar tDCS have both shared and dissociable effects on motor adaptation. The study provides initial causal evidence in speech production that the motor cortex and the cerebellum support different aspects of sensorimotor learning. We propose that motor cortex tDCS drives sensorimotor learning towards previously learned patterns of movement, while cerebellar tDCS focuses sensorimotor learning on error correction.


2020 ◽  
Author(s):  
Tatsuya Umeda ◽  
Tadashi Isa ◽  
Yukio Nishimura

AbstractThe spinal reflex transforms sensory signals to generate muscle activity. However, it is unknown how the motor cortex (MCx) takes the spinal reflex into account when performing voluntary limb movements. We simultaneously recorded the activity of the MCx, afferent neurons, and forelimb muscles in behaving monkeys. We decomposed muscle activity into subcomponents explained by the MCx or afferent activity using linear models. Long preceding activity in the MCx, which is responsible for subsequent afferent activity, had the same spatiotemporal contribution to muscle activity as afferent activity, indicating that the MCx drives muscle activity not only by direct descending activation but also by trans-afferent descending activation. Therefore, the MCx implements internal models that prospectively estimate muscle activation via the spinal reflex for precise movement control.


2018 ◽  
Author(s):  
Chethan Pandarinath ◽  
K. Cora Ames ◽  
Abigail A Russo ◽  
Ali Farshchian ◽  
Lee E Miller ◽  
...  

In the fifty years since Evarts first recorded single neurons in motor cortex of behaving monkeys, great effort has been devoted to understanding their relation to movement. Yet these single neurons exist within a vast network, the nature of which has been largely inaccessible. With advances in recording technologies, algorithms, and computational power, the ability to study network-level phenomena is increasing exponentially. Recent experimental results suggest that the dynamical properties of these networks are critical to movement planning and execution. Here we discuss this dynamical systems perspective, and how it is reshaping our understanding of the motor cortices. Following an overview of key studies in motor cortex, we discuss techniques to uncover the “latent factors” underlying observed neural population activity. Finally, we discuss efforts to leverage these factors to improve the performance of brain-machine interfaces, promising to make these findings broadly relevant to neuroengineering as well as systems neuroscience.


2018 ◽  
Vol 30 (4) ◽  
pp. 540-551 ◽  
Author(s):  
Daniel R. Lametti ◽  
Harriet J. Smith ◽  
Phoebe F. Freidin ◽  
Kate E. Watkins

The motor cortex and cerebellum are thought to be critical for learning and maintaining motor behaviors. Here we use transcranial direct current stimulation (tDCS) to test the role of the motor cortex and cerebellum in sensorimotor learning in speech. During productions of “head,” “bed,” and “dead,” the first formant of the vowel sound was altered in real time toward the first formant of the vowel sound in “had,” “bad,” and “dad.” Compensatory changes in first and second formant production were used as a measure of motor adaptation. tDCS to either the motor cortex or the cerebellum improved sensorimotor learning in speech compared with sham stimulation ( n = 20 in each group). However, in the case of cerebellar tDCS, production changes were restricted to the source of the acoustical error (i.e., the first formant). Motor cortex tDCS drove production changes that offset errors in the first formant, but unlike cerebellar tDCS, adaptive changes in the second formant also occurred. The results suggest that motor cortex and cerebellar tDCS have both shared and dissociable effects on motor adaptation. The study provides initial causal evidence in speech production that the motor cortex and the cerebellum support different aspects of sensorimotor learning. We propose that motor cortex tDCS drives sensorimotor learning toward previously learned patterns of movement, whereas cerebellar tDCS focuses sensorimotor learning on error correction.


Nature ◽  
2012 ◽  
Vol 484 (7395) ◽  
pp. 473-478 ◽  
Author(s):  
D. Huber ◽  
D. A. Gutnisky ◽  
S. Peron ◽  
D. H. O’Connor ◽  
J. S. Wiegert ◽  
...  

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