Spike synchronization and firing rate in a population of motor cortical neurons in relation to movement direction and reaction time

2003 ◽  
Vol 88 (5) ◽  
pp. 360-373 ◽  
Author(s):  
F. Grammont ◽  
A. Riehle
1998 ◽  
Vol 95 (26) ◽  
pp. 15706-15711 ◽  
Author(s):  
N. G. Hatsopoulos ◽  
C. L. Ojakangas ◽  
L. Paninski ◽  
J. P. Donoghue

2009 ◽  
Vol 10 (S1) ◽  
Author(s):  
Adrián Ponce-Alvarez ◽  
Bjørg Elisabeth Kilavik ◽  
Alexa Riehle

1983 ◽  
Vol 50 (6) ◽  
pp. 1359-1379 ◽  
Author(s):  
G. Spidalieri ◽  
L. Busby ◽  
Y. Lamarre

Single-unit recordings from motor cortex (area 4) were obtained before and after dentate lesion in two monkeys executing fast elbow flexions and extensions in response to randomly presented visual, auditory, and somesthetic stimuli. There were no starting or ending reference points or preparatory signals. Monkeys were trained to perform movements larger than 15 degrees within 500 ms of the stimulus presentation. After electrolytic lesion of the dentate nucleus ipsilateral to the trained arm, changes in reaction time (RT) were observed. Mean daily RTs of movements triggered by light and sound were lengthened by 50-70 ms. RTs of movements triggered by somesthetic stimuli were not changed in one monkey, whereas a small increase of only 20 ms was observed in the other animal. Spontaneous firing of precentral neurons was about the same before and after dentate lesion. However, movement-related responses of cortical neurons were affected by the lesion. Whenever there was an increase in RT according to the triggering stimuli, a corresponding increase in the response time of neurons (RS) appeared. Both RS and RT increased by the same amount when movements were triggered by visual and auditory stimuli, whereas they remained about the same when somesthetic stimuli were used to trigger movements. In contrast, the time interval between the appearance of the change of neuronal firing and onset of arm displacement (RM) was not modified after the lesion. Gating of sensory conditioning inputs and modification of RT by the presentation of more than one stimulus were not abolished by dentate lesion. As a whole, the effects of dentate lesion on motor cortical neurons are consistent with the hypothesis that the neocerebellum controls the initiation of simple ballistic limb movements by controlling the discharge of motor cortex neurons. The effects could be attributed to the withdrawal of a facilitatory influence of dentate neurons on the motor cortical cells, particularly for movements triggered by teleceptive inputs.


2009 ◽  
Vol 29 (44) ◽  
pp. 13870-13882 ◽  
Author(s):  
J. Rickert ◽  
A. Riehle ◽  
A. Aertsen ◽  
S. Rotter ◽  
M. P. Nawrot

2019 ◽  
Author(s):  
Eric M. Trautmann ◽  
Daniel J. O’Shea ◽  
Xulu Sun ◽  
James H. Marshel ◽  
Ailey Crow ◽  
...  

AbstractCalcium imaging has rapidly developed into a powerful tool for recording from large populations of neurons in vivo. Imaging in rhesus macaque motor cortex can enable the discovery of new principles of motor cortical function and can inform the design of next generation brain-computer interfaces (BCIs). Surface two-photon (2P) imaging, however, cannot presently access somatic calcium signals of neurons from all layers of macaque motor cortex due to photon scattering. Here, we demonstrate an implant and imaging system capable of chronic, motion-stabilized two-photon (2P) imaging of calcium signals from in macaques engaged in a motor task. By imaging apical dendrites, some of which originated from deep layer 5 neurons, as as well as superficial cell bodies, we achieved optical access to large populations of deep and superficial cortical neurons across dorsal premotor (PMd) and gyral primary motor (M1) cortices. Dendritic signals from individual neurons displayed tuning for different directions of arm movement, which was stable across many weeks. Combining several technical advances, we developed an optical BCI (oBCI) driven by these dendritic signals and successfully decoded movement direction online. By fusing 2P functional imaging with CLARITY volumetric imaging, we verify that an imaged dendrite, which contributed to oBCI decoding, originated from a putative Betz cell in motor cortical layer 5. This approach establishes new opportunities for studying motor control and designing BCIs.


2017 ◽  
Vol 114 (24) ◽  
pp. E4841-E4850 ◽  
Author(s):  
Arjun Ramakrishnan ◽  
Yoon Woo Byun ◽  
Kyle Rand ◽  
Christian E. Pedersen ◽  
Mikhail A. Lebedev ◽  
...  

Rewards are known to influence neural activity associated with both motor preparation and execution. This influence can be exerted directly upon the primary motor (M1) and somatosensory (S1) cortical areas via the projections from reward-sensitive dopaminergic neurons of the midbrain ventral tegmental areas. However, the neurophysiological manifestation of reward-related signals in M1 and S1 are not well understood. Particularly, it is unclear how the neurons in these cortical areas multiplex their traditional functions related to the control of spatial and temporal characteristics of movements with the representation of rewards. To clarify this issue, we trained rhesus monkeys to perform a center-out task in which arm movement direction, reward timing, and magnitude were manipulated independently. Activity of several hundred cortical neurons was simultaneously recorded using chronically implanted microelectrode arrays. Many neurons (9–27%) in both M1 and S1 exhibited activity related to reward anticipation. Additionally, neurons in these areas responded to a mismatch between the reward amount given to the monkeys and the amount they expected: A lower-than-expected reward caused a transient increase in firing rate in 60–80% of the total neuronal sample, whereas a larger-than-expected reward resulted in a decreased firing rate in 20–35% of the neurons. Moreover, responses of M1 and S1 neurons to reward omission depended on the direction of movements that led to those rewards. These observations suggest that sensorimotor cortical neurons corepresent rewards and movement-related activity, presumably to enable reward-based learning.


1999 ◽  
Vol 33 (1) ◽  
pp. 33-40 ◽  
Author(s):  
Kadrul Huda ◽  
Thucidydes L. Salunga ◽  
Syed A. Chowdhury ◽  
Takashi Kawashima ◽  
Ken’ichi Matsunami

Author(s):  
Maryam Owjfard ◽  
Zohreh Taghadosi ◽  
Mohammad Reza Bigdeli ◽  
Anahid Safari ◽  
Asadollah Zarifkar ◽  
...  

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