Discernible effects of tDCS over the primary motor and posterior parietal cortex on different stages of motor learning

2022 ◽  
Author(s):  
Guadalupe Nathzidy Rivera-Urbina ◽  
Andrés Molero-Chamizo ◽  
Michael A. Nitsche
Keyword(s):  
Motor Learning ◽  
Parietal Cortex ◽  
Posterior Parietal Cortex ◽  
Posterior Parietal

scholarly journals Neuronal representation of saccadic error in macaque posterior parietal cortex (PPC)

eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
Yang Zhou ◽  
Yining Liu ◽  
Haidong Lu ◽  
Si Wu ◽  
Mingsha Zhang
Keyword(s):  
Motor Learning ◽  
Parietal Cortex ◽  
Error Detection ◽  
Posterior Parietal Cortex ◽  
Spatial Perception ◽  
Saccadic Response ◽  
Motor Intention ◽  
Self Recognition ◽  
Posterior Parietal ◽  
Neuronal Computation

Motor control, motor learning, self-recognition, and spatial perception all critically depend on the comparison of motor intention to the actually executed movement. Despite our knowledge that the brainstem-cerebellum plays an important role in motor error detection and motor learning, the involvement of neocortex remains largely unclear. Here, we report the neuronal computation and representation of saccadic error in macaque posterior parietal cortex (PPC). Neurons with persistent pre- and post-saccadic response (PPS) represent the intended end-position of saccade; neurons with late post-saccadic response (LPS) represent the actual end-position of saccade. Remarkably, after the arrival of the LPS signal, the PPS neurons’ activity becomes highly correlated with the discrepancy between intended and actual end-position, and with the probability of making secondary (corrective) saccades. Thus, this neuronal computation might underlie the formation of saccadic error signals in PPC for speeding up saccadic learning and leading the occurrence of secondary saccade.

The posterior parietal cortex: A cortical „driver“ for bimanual motor learning?

2006 ◽  
Vol 37 (01) ◽  
Author(s):  
A Rilk ◽  
F Andres ◽  
F Hummel ◽  
J Hansmann ◽  
M Hallett ◽  
...  
Keyword(s):  
Motor Learning ◽  
Parietal Cortex ◽  
Posterior Parietal Cortex ◽  
Posterior Parietal

The posterior parietal cortex: A cortical “driver” for bimanual motor learning?

2007 ◽  
Vol 118 (4) ◽  
pp. e86-e87
Author(s):  
A. Rilk ◽  
F. Andres ◽  
F. Hummel ◽  
J. Hansmann ◽  
M. Hallett ◽  
...  
Keyword(s):  
Motor Learning ◽  
Parietal Cortex ◽  
Posterior Parietal Cortex ◽  
Posterior Parietal

Posterior parietal cortex mediates encoding processes in change blindness

2009 ◽  
Author(s):  
Philip Tseng ◽  
Cassidy Sterling ◽  
Adam Cooper ◽  
Bruce Bridgeman ◽  
Neil G. Muggleton ◽  
...  
Keyword(s):  
Parietal Cortex ◽  
Posterior Parietal Cortex ◽  
Change Blindness ◽  
Posterior Parietal

The Grasp Cell Hypothesis: Near-miss effect points to common neurological machinery in posterior parietal cortex for controllable objects and concepts

2018 ◽  
Author(s):  
Imogen M Kruse
Keyword(s):  
Parietal Cortex ◽  
Posterior Parietal Cortex ◽  
Near Miss ◽  
Illusion Of Control ◽  
Gambling Behaviour ◽  
Drug Seeking ◽  
Spatial Influence ◽  
Reward Probability ◽  
Posterior Parietal ◽  
Action Value

The near-miss effect in gambling behaviour occurs when an outcome which is close to a win outcome invigorates gambling behaviour notwithstanding lack of associated reward. In this paper I postulate that the processing of concepts which are deemed controllable is rooted in neurological machinery located in the posterior parietal cortex specialised for the processing of objects which are immediately actionable or controllable because they are within reach. I theorise that the use of a common machinery facilitates spatial influence on the perception of concepts such that the win outcome which is 'almost complete' is perceived as being 'almost within reach'. The perceived realisability of the win increases subjective reward probability and the associated expected action value which impacts decision-making and behaviour. This novel hypothesis is the first to offer a neurological model which can comprehensively explain many empirical findings associated with the near-miss effect as well as other gambling phenomena such as the ‘illusion of control’. Furthermore, when extended to other compulsive behaviours such as drug addiction, the model can offer an explanation for continued drug-seeking following devaluation and for the increase in cravings in response to perceived opportunity to self-administer, neither of which can be explained by simple reinforcement models alone. This paper therefore provides an innovative and unifying perspective for the study and treatment of behavioural and substance addictions.

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