Effects of frontal cortex lesions on action sequence learning in the rat

2007 ◽  
Vol 25 (9) ◽  
pp. 2905-2915 ◽  
Author(s):  
Kathleen R. Bailey ◽  
Robert G. Mair
2014 ◽  
Vol 125 ◽  
pp. S28
Author(s):  
T. Shimizu ◽  
R. Hanajima ◽  
R. Tsutsumi ◽  
Y. Shirota ◽  
M. Hamada ◽  
...  

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Anne L. Collins ◽  
Venuz Y. Greenfield ◽  
Jeffrey K. Bye ◽  
Kay E. Linker ◽  
Alice S. Wang ◽  
...  

2019 ◽  
Author(s):  
Eric Garr

Animals engage in intricately woven and choreographed action sequences that are constructed from trial-and-error learning. The mechanisms by which the brain links together individual actions which are later recalled as fluid chains of behavior are not fully understood, but there is broad consensus that the basal ganglia play a crucial role in this process. This paper presents a comprehensive review of the role of the basal ganglia in action sequencing, with a focus on whether the computational framework of reinforcement learning can capture key behavioral features of sequencing and the neural mechanisms that underlie them. While a simple neurocomputational model of reinforcement learning can capture key features of action sequence learning, this model is not sufficient to capture goal-directed control of sequences or their hierarchical representation. The hierarchical structure of action sequences, in particular, poses a challenge for building better models of action sequencing, and it is in this regard that further investigations into basal ganglia information processing may be informative.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
A. J. Rybicki ◽  
J. M. Galea ◽  
B. A. Schuster ◽  
C. Hiles ◽  
C. Fabian ◽  
...  

AbstractAtypical motor learning has been suggested to underpin the development of motoric challenges (e.g., handwriting difficulties) in autism. Bayesian accounts of autistic cognition propose a mechanistic explanation for differences in the learning process in autism. Specifically, that autistic individuals overweight incoming, at the expense of prior, information and are thus less likely to (a) build stable expectations of upcoming events and (b) react to statistically surprising events. Although Bayesian accounts have been suggested to explain differences in learning across a range of domains, to date, such accounts have not been extended to motor learning. 28 autistic and 35 non-autistic controls (IQ > 70) completed a computerised task in which they learned sequences of actions. On occasional “surprising” trials, an expected action had to be replaced with an unexpected action. Sequence learning was indexed as the reaction time difference between blocks which featured a predictable sequence and those that did not. Surprise-related slowing was indexed as the reaction time difference between surprising and unsurprising trials. No differences in sequence-learning or surprise-related slowing were observed between the groups. Bayesian statistics provided anecdotal to moderate evidence to support the conclusion that sequence learning and surprise-related slowing were comparable between the two groups. We conclude that individuals with autism do not show atypicalities in response to surprising events in the context of motor sequence-learning. These data demand careful consideration of the way in which Bayesian accounts of autism can (and cannot) be extended to the domain of motor learning.


2013 ◽  
Vol 124 (10) ◽  
pp. e105
Author(s):  
T. Shimizu ◽  
R. Hanajima ◽  
R. Tsutsumi ◽  
Y. Shirota ◽  
N. Tanaka ◽  
...  

1998 ◽  
Vol 70 (1-2) ◽  
pp. 137-149 ◽  
Author(s):  
O. Hikosaka ◽  
K. Miyashita ◽  
S. Miyachi ◽  
K. Sakai ◽  
X. Lu

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