scholarly journals The basal ganglia can control learned motor sequences independently of motor cortex

2019 ◽  
Author(s):  
Ashesh K. Dhawale ◽  
Steffen B. E. Wolff ◽  
Raymond Ko ◽  
Bence P. Ölveczky
Keyword(s):  
Basal Ganglia ◽  
Motor Cortex ◽  
Motor Skills ◽  
Neural Activity ◽  
Action Selection ◽  
Kinematic Structure ◽  
Motor Circuits ◽  
Control Functions ◽  
Neural Representations ◽  
Learned Behaviors

SummaryHow the basal ganglia contribute to the execution of learned motor skills has been thoroughly investigated. The two dominant models that have emerged posit roles for the basal ganglia in action selection and in the modulation of movement vigor. Here we test these models in rats trained to execute highly stereotyped and idiosyncratic task-specific motor sequences. Recordings and manipulations of neural activity in the striatum were not well explained by either model, and suggested that the basal ganglia, in particular its sensorimotor arm, are crucial for controlling the detailed kinematic structure of the learned behaviors. Importantly, the neural representations in the striatum, and the control functions they subserve, did not depend on the motor cortex. Taken together, these results extend our understanding of basal ganglia function, by suggesting that they can control and modulate lower-level subcortical motor circuits on a moment-by-moment basis to generate stereotyped learned motor sequences.

scholarly journals Remembrance of things practiced with fast and slow learning in cortical and subcortical pathways

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
James M. Murray ◽  
G. Sean Escola
Keyword(s):  
Motor Cortex ◽  
Motor Learning ◽  
Motor Skills ◽  
Neural Mechanisms ◽  
Neural Basis ◽  
Brain Areas ◽  
Multiple Timescales ◽  
Learned Behaviors ◽  
Future Learning ◽  
Slow Learning

AbstractThe learning of motor skills unfolds over multiple timescales, with rapid initial gains in performance followed by a longer period in which the behavior becomes more refined, habitual, and automatized. While recent lesion and inactivation experiments have provided hints about how various brain areas might contribute to such learning, their precise roles and the neural mechanisms underlying them are not well understood. In this work, we propose neural- and circuit-level mechanisms by which motor cortex, thalamus, and striatum support motor learning. In this model, the combination of fast cortical learning and slow subcortical learning gives rise to a covert learning process through which control of behavior is gradually transferred from cortical to subcortical circuits, while protecting learned behaviors that are practiced repeatedly against overwriting by future learning. Together, these results point to a new computational role for thalamus in motor learning and, more broadly, provide a framework for understanding the neural basis of habit formation and the automatization of behavior through practice.

Repetitive Transcranial Magnetic Stimulation to the Primary Motor Cortex Interferes with Motor Learning by Observing

2009 ◽  
Vol 21 (5) ◽  
pp. 1013-1022 ◽  
Author(s):  
Liana E. Brown ◽  
Elizabeth T. Wilson ◽  
Paul L. Gribble
Keyword(s):  
Transcranial Magnetic Stimulation ◽  
Motor Cortex ◽  
Motor Learning ◽  
Motor Skills ◽  
Magnetic Stimulation ◽  
Primary Motor Cortex ◽  
Repetitive Transcranial Magnetic Stimulation ◽  
Cortical Region ◽  
Robot Arm ◽  
Neural Representations

Neural representations of novel motor skills can be acquired through visual observation. We used repetitive transcranial magnetic stimulation (rTMS) to test the idea that this “motor learning by observing” is based on engagement of neural processes for learning in the primary motor cortex (M1). Human subjects who observed another person learning to reach in a novel force environment imposed by a robot arm performed better when later tested in the same environment than subjects who observed movements in a different environment. rTMS applied to M1 after observation reduced the beneficial effect of observing congruent forces, and eliminated the detrimental effect of observing incongruent forces. Stimulation of a control site in the frontal cortex had no effect on reaching. Our findings represent the first direct evidence that neural representations of motor skills in M1, a cortical region whose role has been firmly established for active motor learning, also underlie motor learning by observing.

scholarly journals Proactive Interference as a Result of Persisting Neural Representations of Previously Learned Motor Skills in Primary Motor Cortex

2006 ◽  
Vol 18 (12) ◽  
pp. 2167-2176 ◽  
Author(s):  
Nicholas Cothros ◽  
Stefan Köhler ◽  
Erin W. Dickie ◽  
Seyed M. Mirsattari ◽  
Paul L. Gribble
Keyword(s):  
Motor Cortex ◽  
Proactive Interference ◽  
Motor Skills ◽  
Magnetic Stimulation ◽  
Primary Motor Cortex ◽  
Repetitive Transcranial Magnetic Stimulation ◽  
Dynamic Environments ◽  
Robotic Arm ◽  
Neural Basis ◽  
Neural Representations

Learning to control movements in different dynamic environments is marked by proactive interference; learning a first skill interferes with the subsequent learning of a second one. The neural basis of this effect is poorly understood. We tested the idea that proactive interference results from persisting neural representations of previously learned skills in the primary motor cortex (M1). We used repetitive transcranial magnetic stimulation (rTMS) of M1 to disrupt retention of a recently learned motor skill. If interference results from the retention of this skill then its disruption should be associated with reduced interference. Subjects reached to targets while interacting with a robotic arm that applied force fields to the limb. Fifteen minutes of 1-Hz rTMS to M1 impaired the retention of a first force field, and more importantly, reduced proactive interference when subjects learned a second one. Our findings suggest that retention and interference are linked at the level of M1.

scholarly journals Remembrance of things practiced: Fast and slow learning in cortical and subcortical pathways

2019 ◽  
Author(s):  
James M. Murray ◽  
G. Sean Escola
Keyword(s):  
Motor Cortex ◽  
Motor Skills ◽  
Learning Process ◽  
Neural Mechanisms ◽  
Neural Basis ◽  
Brain Areas ◽  
Multiple Timescales ◽  
Learned Behaviors ◽  
Future Learning ◽  
Slow Learning

The learning of motor skills unfolds over multiple timescales, with rapid initial gains in performance followed by a longer period in which the behavior becomes more refined, habitual, and automatized. While recent lesion and inactivation experiments have provided hints about how various brain areas might contribute to such learning, their precise roles and the neural mechanisms underlying them are not well understood. In this work, we propose neural- and circuit-level mechanisms by which motor cortex, thalamus, and striatum support such learning. In this model, the combination of fast cortical learning and slow subcortical learning gives rise to a covert learning process through which control of behavior is gradually transferred from cortical to subcortical circuits, while protecting learned behaviors that are practiced repeatedly against overwriting by future learning. Together, these results point to a new computational role for thalamus in motor learning, and, more broadly, provide a framework for understanding the neural basis of habit formation and the automatization of behavior through practice.

Focal Photothrombotic Lesion of the Rat Motor Cortex Increases BDNF Levels in Motor-Sensory Cortical Areas Not Accompanied by Recovery of Forelimb Motor Skills

2007 ◽  
Vol 24 (8) ◽  
pp. 1362-1377 ◽  
Author(s):  
Dorota Sulejczak ◽  
Ewelina Ziemlińska ◽  
Julita Czarkowska-Bauch ◽  
Ewa Nosecka ◽  
Ryszard Strzalkowski ◽  
...  
Keyword(s):  
Motor Cortex ◽  
Motor Skills ◽  
Cortical Areas

scholarly journals An Avian Basal Ganglia-Forebrain Circuit Contributes Differentially to Syllable Versus Sequence Variability of Adult Bengalese Finch Song

2009 ◽  
Vol 101 (6) ◽  
pp. 3235-3245 ◽  
Author(s):  
Cara M. Hampton ◽  
Jon T. Sakata ◽  
Michael S. Brainard
Keyword(s):  
Basal Ganglia ◽  
Syllable Structure ◽  
Skill Learning ◽  
Behavioral Variability ◽  
Neural Pathways ◽  
Sequence Variability ◽  
Social Modulation ◽  
The Social ◽  
Learned Behaviors ◽  
Magnocellular Nucleus

Behavioral variability is important for motor skill learning but continues to be present and actively regulated even in well-learned behaviors. In adult songbirds, two types of song variability can persist and are modulated by social context: variability in syllable structure and variability in syllable sequencing. The degree to which the control of both types of adult variability is shared or distinct remains unknown. The output of a basal ganglia-forebrain circuit, LMAN (the lateral magnocellular nucleus of the anterior nidopallium), has been implicated in song variability. For example, in adult zebra finches, neurons in LMAN actively control the variability of syllable structure. It is unclear, however, whether LMAN contributes to variability in adult syllable sequencing because sequence variability in adult zebra finch song is minimal. In contrast, Bengalese finches retain variability in both syllable structure and syllable sequencing into adulthood. We analyzed the effects of LMAN lesions on the variability of syllable structure and sequencing and on the social modulation of these forms of variability in adult Bengalese finches. We found that lesions of LMAN significantly reduced the variability of syllable structure but not of syllable sequencing. We also found that LMAN lesions eliminated the social modulation of the variability of syllable structure but did not detect significant effects on the modulation of sequence variability. These results show that LMAN contributes differentially to syllable versus sequence variability of adult song and suggest that these forms of variability are regulated by distinct neural pathways.

scholarly journals Single units and conscious vision

1998 ◽  
Vol 353 (1377) ◽  
pp. 1801-1818 ◽  
Author(s):  
◽  
N. K. Logothetis
Keyword(s):  
Binocular Rivalry ◽  
Neural Activity ◽  
Visual Awareness ◽  
Physiological Data ◽  
Neural Basis ◽  
Binocular Fusion ◽  
Neural Representations ◽  
Multistable Perception ◽  
Visual Areas ◽  
Psychophysical Studies

Figures that can be seen in more than one way are invaluable tools for the study of the neural basis of visual awareness, because such stimuli permit the dissociation of the neural responses that underlie what we perceive at any given time from those forming the sensory representation of a visual pattern. To study the former type of responses, monkeys were subjected to binocular rivalry, and the response of neurons in a number of different visual areas was studied while the animals reported their alternating percepts by pulling levers. Perception–related modulations of neural activity were found to occur to different extents in different cortical visual areas. The cells that were affected by suppression were almost exclusively binocular, and their proportion was found to increase in the higher processing stages of the visual system. The strongest correlations between neural activity and perception were observed in the visual areas of the temporal lobe. A strikingly large number of neurons in the early visual areas remained active during the perceptual suppression of the stimulus, a finding suggesting that conscious visual perception might be mediated by only a subset of the cells exhibiting stimulus selective responses. These physiological findings, together with a number of recent psychophysical studies, offer a new explanation of the phenomenon of binocular rivalry. Indeed, rivalry has long been considered to be closely linked with binocular fusion and stereopsis, and the sequences of dominance and suppression have been viewed as the result of competition between the two monocular channels. The physiological data presented here are incompatible with this interpretation. Rather than reflecting interocular competition, the rivalry is most probably between the two different central neural representations generated by the dichoptically presented stimuli. The mechanisms of rivalry are probably the same as, or very similar to, those underlying multistable perception in general, and further physiological studies might reveal a much about the neural mechanisms of our perceptual organization.

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