Saccade Adaptation in Response to Altered Arm Dynamics

2003 ◽  
Vol 90 (6) ◽  
pp. 4016-4021 ◽  
Author(s):  
Thrishantha Nanayakkara ◽  
Reza Shadmehr

The delays in sensorimotor pathways pose a formidable challenge to the implementation of stable error feedback control, and yet the intact brain has little trouble maintaining limb stability. How is this achieved? One idea is that feedback control depends not only on delayed proprioceptive feedback but also on internal models of limb dynamics. In theory, an internal model allows the brain to predict limb position. Earlier we had found that during reaching, the brain estimates hand position in real-time in a coordinate system that can be used for generating saccades. Here we tested the idea that the estimate of hand position, as expressed through saccades, depends on an internal model that adapts to dynamics of the arm. We focused on the behavior of the eyes as perturbations were applied to the unseen hand. We found that when the hand was perturbed from stable posture with a 100-ms force pulse of random direction and magnitude, a saccade was generated on average at 182 ms postpulse onset to a position that was an unbiased estimate of real-time hand position. To test whether planning of saccades depended on an internal model of arm dynamics, arm dynamics were altered either predictably or unpredictably during the postpulse period. When arm dynamics were predictable, saccade amplitudes changed to reflect the change in the arm's behavior. We suggest that proprioceptive feedback from the arm is integrated into an adaptable internal model that computes an estimate of current hand position in eye-centered coordinates.

2007 ◽  
Vol 97 (2) ◽  
pp. 1527-1545 ◽  
Author(s):  
Aaron J. Suminski ◽  
Stephen M. Rao ◽  
Kristine M. Mosier ◽  
Robert A. Scheidt

In identical experiments in and out of a MR scanner, we recorded functional magnetic resonance imaging and electromyographic correlates of wrist stabilization against constant and time-varying mechanical perturbations. Positioning errors were greatest while stabilizing random torques. Wrist muscle activity lagged changes in joint angular velocity at latencies suggesting trans-cortical reflex action. Drift in stabilized hand positions gave rise to frequent, accurately directed, corrective movements, suggesting that the brain maintains separate representations of desired wrist angle for feedback control of posture and the generation of discrete corrections. Two patterns of neural activity were evident in the blood-oxygenation-level-dependent (BOLD) time series obtained during stabilization. A cerebello-thalamo-cortical network showed significant activity whenever position errors were present. Here, changes in activation correlated with moment-by-moment changes in position errors (not force), implicating this network in the feedback control of hand position. A second network, showing elevated activity during stabilization whether errors were present or not, included prefrontal cortex, rostral dorsal premotor and supplementary motor area cortices, and inferior aspects of parietal cortex. BOLD activation in some of these regions correlated with positioning errors integrated over a longer time-frame consistent with optimization of feedback performance via adjustment of the behavioral goal (feedback setpoint) and the planning and execution of internally generated motor actions. The finding that nonoverlapping networks demonstrate differential sensitivity to kinematic performance errors over different time scales supports the hypothesis that in stabilizing the hand, the brain recruits distinct neural systems for feedback control of limb position and for evaluation/adjustment of controller parameters in response to persistent errors.


2020 ◽  
Vol 20 (3) ◽  
pp. 174-183
Author(s):  
Bushra Nabi ◽  
Saleha Rehman ◽  
Faheem Hyder Pottoo ◽  
Sanjula Baboota ◽  
Javed Ali

: NeuroAIDS, a disease incorporating both infectious and neurodegenerative pathways, is still a formidable challenge for the researchers to deal with. The primary concern for the treatment of neuroAIDS still remains the inaccessibility of the viral reservoir, making it indispensable for novel techniques to be continuously innovated. Since the brain serves as a reservoir for viral replication, it is pragmatic and a prerequisite to overcome the related barriers in order to improve the drug delivery to the brain. The current treatment ideology is based on the combinatorial approach of a mocktail of antiretroviral drugs. However, complete eradication of the disease could not be achieved. Thereby the arena of gene-based cellular delivery is trending and has created a niche for itself in the present scenario. To establish the supremacy of gene delivery, it is advisable to have a better understanding of the molecular mechanism involved in the due process. The mechanism associated with the activity of the anti-HIV gene lies in their intrinsic property to impart resistance to the HIV infection by targeting the viral entry channels. This review principally emphasizes on different types of gene therapies explored so far for the management of AIDS and its associated neurological conditions. Therefore it could rightly be said that we are at the crossroad where the need of the hour is to develop novel strategies for curbing AIDS and its associated neurological conditions.


2020 ◽  
Vol 5 (6) ◽  
pp. 1156-1162
Author(s):  
Anirudh Gautam ◽  
Jason A. Brant ◽  
Michael J. Ruckenstein ◽  
Steven J. Eliades

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 3955
Author(s):  
Jung-Cheng Yang ◽  
Chun-Jung Lin ◽  
Bing-Yuan You ◽  
Yin-Long Yan ◽  
Teng-Hu Cheng

Most UAVs rely on GPS for localization in an outdoor environment. However, in GPS-denied environment, other sources of localization are required for UAVs to conduct feedback control and navigation. LiDAR has been used for indoor localization, but the sampling rate is usually too low for feedback control of UAVs. To compensate this drawback, IMU sensors are usually fused to generate high-frequency odometry, with only few extra computation resources. To achieve this goal, a real-time LiDAR inertial odometer system (RTLIO) is developed in this work to generate high-precision and high-frequency odometry for the feedback control of UAVs in an indoor environment, and this is achieved by solving cost functions that consist of the LiDAR and IMU residuals. Compared to the traditional LIO approach, the initialization process of the developed RTLIO can be achieved, even when the device is stationary. To further reduce the accumulated pose errors, loop closure and pose-graph optimization are also developed in RTLIO. To demonstrate the efficacy of the developed RTLIO, experiments with long-range trajectory are conducted, and the results indicate that the RTLIO can outperform LIO with a smaller drift. Experiments with odometry benchmark dataset (i.e., KITTI) are also conducted to compare the performance with other methods, and the results show that the RTLIO can outperform ALOAM and LOAM in terms of exhibiting a smaller time delay and greater position accuracy.


2021 ◽  
Vol 165 ◽  
pp. 112218
Author(s):  
Rohit Kumar ◽  
Pramila Gautam ◽  
Shivam Gupta ◽  
R.L. Tanna ◽  
Praveenlal Edappala ◽  
...  

2020 ◽  
Vol 53 (2) ◽  
pp. 8519-8524
Author(s):  
G. Hassan ◽  
A. Chemori ◽  
L. Chikh ◽  
P.E. Hervé ◽  
M. El Rafei ◽  
...  

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