Resting-state brain network features associated with short-term skill learning ability in humans and the influence of N -methyl- d -aspartate receptor antagonism

Graph theoretical functional magnetic resonance imaging (fMRI) studies have demonstrated that brain networks reorganize significantly during motor skill acquisition, yet the associations between motor learning ability, brain network features, and the underlying biological mechanisms remain unclear....

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Published in:Network neuroscience (Cambridge, Mass.) Vol. 2; no. 4; pp. 464 - 480
Main Authors: Zang, Zhenxiang, Geiger, Lena S., Braun, Urs, Cao, Hengyi, Zangl, Maria, Schäfer, Axel, Moessnang, Carolin, Ruf, Matthias, Reis, Janine, Schweiger, Janina I., Dixson, Luanna, Moscicki, Alexander, Schwarz, Emanuel, Meyer-Lindenberg, Andreas, Tost, Heike
Format: Journal Article
Language:English
Published: One Rogers Street, Cambridge, MA 02142-1209, USA MIT Press 01-01-2018
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Abstract Graph theoretical functional magnetic resonance imaging (fMRI) studies have demonstrated that brain networks reorganize significantly during motor skill acquisition, yet the associations between motor learning ability, brain network features, and the underlying biological mechanisms remain unclear. In the current study, we applied a visually guided sequential pinch force learning task and graph theoretical analyses to investigate the associations between short-term motor learning ability and resting-state brain network metrics in 60 healthy subjects. We further probed the test-retest reliability ( = 26) and potential effects of the -methyl- -aspartate (NMDA) antagonist ketamine ( = 19) in independent healthy volunteers. Our results show that the improvement of motor performance after short-term training was positively correlated with small-worldness ( = 0.032) and global efficiency ( = 0.025), whereas negatively correlated with characteristic path length ( = 0.014) and transitivity ( = 0.025). In addition, using network-based statistics (NBS), we identified a learning ability–associated ( = 0.037) and ketamine-susceptible ( = 0.027) cerebellar-cortical network with fair to good reliability (intraclass correlation coefficient [ICC] > 0.7) and higher functional connectivity in better learners. Our results provide new evidence for the association of intrinsic brain network features with motor learning and suggest a role of NMDA-related glutamatergic processes in learning-associated subnetworks. Learning a new motor skill prompts immediate reconfigurations of distributed brain networks followed by adaptive changes in intrinsic brain circuits related to synaptic plasticity. Here, we identify global brain network properties and a cerebellar-cortical functional subnetwork that are both significantly associated with motor learning ability in a previously trained visuomotor task in humans. We further show that the associated functional subnetwork connectivity but not the global brain network properties are susceptible to ketamine. Our findings suggest a distinct functional role for learning-related global versus local network metrics and support the idea of a preferential susceptibility of learning-associated subnetworks to -methyl- -aspartate antagonist and plasticity-related consolidation effects.
AbstractList Graph theoretical functional magnetic resonance imaging (fMRI) studies have demonstrated that brain networks reorganize significantly during motor skill acquisition, yet the associations between motor learning ability, brain network features, and the underlying biological mechanisms remain unclear. In the current study, we applied a visually guided sequential pinch force learning task and graph theoretical analyses to investigate the associations between short-term motor learning ability and resting-state brain network metrics in 60 healthy subjects. We further probed the test-retest reliability (n = 26) and potential effects of the N-methyl-d-aspartate (NMDA) antagonist ketamine (n = 19) in independent healthy volunteers. Our results show that the improvement of motor performance after short-term training was positively correlated with small-worldness (p = 0.032) and global efficiency (p = 0.025), whereas negatively correlated with characteristic path length (p = 0.014) and transitivity (p = 0.025). In addition, using network-based statistics (NBS), we identified a learning ability–associated (p = 0.037) and ketamine-susceptible (p = 0.027) cerebellar-cortical network with fair to good reliability (intraclass correlation coefficient [ICC] > 0.7) and higher functional connectivity in better learners. Our results provide new evidence for the association of intrinsic brain network features with motor learning and suggest a role of NMDA-related glutamatergic processes in learning-associated subnetworks. Learning a new motor skill prompts immediate reconfigurations of distributed brain networks followed by adaptive changes in intrinsic brain circuits related to synaptic plasticity. Here, we identify global brain network properties and a cerebellar-cortical functional subnetwork that are both significantly associated with motor learning ability in a previously trained visuomotor task in humans. We further show that the associated functional subnetwork connectivity but not the global brain network properties are susceptible to ketamine. Our findings suggest a distinct functional role for learning-related global versus local network metrics and support the idea of a preferential susceptibility of learning-associated subnetworks to N-methyl-d-aspartate antagonist and plasticity-related consolidation effects.
Graph theoretical functional magnetic resonance imaging (fMRI) studies have demonstrated that brain networks reorganize significantly during motor skill acquisition, yet the associations between motor learning ability, brain network features, and the underlying biological mechanisms remain unclear. In the current study, we applied a visually guided sequential pinch force learning task and graph theoretical analyses to investigate the associations between short-term motor learning ability and resting-state brain network metrics in 60 healthy subjects. We further probed the test-retest reliability ( = 26) and potential effects of the -methyl- -aspartate (NMDA) antagonist ketamine ( = 19) in independent healthy volunteers. Our results show that the improvement of motor performance after short-term training was positively correlated with small-worldness ( = 0.032) and global efficiency ( = 0.025), whereas negatively correlated with characteristic path length ( = 0.014) and transitivity ( = 0.025). In addition, using network-based statistics (NBS), we identified a learning ability–associated ( = 0.037) and ketamine-susceptible ( = 0.027) cerebellar-cortical network with fair to good reliability (intraclass correlation coefficient [ICC] > 0.7) and higher functional connectivity in better learners. Our results provide new evidence for the association of intrinsic brain network features with motor learning and suggest a role of NMDA-related glutamatergic processes in learning-associated subnetworks. Learning a new motor skill prompts immediate reconfigurations of distributed brain networks followed by adaptive changes in intrinsic brain circuits related to synaptic plasticity. Here, we identify global brain network properties and a cerebellar-cortical functional subnetwork that are both significantly associated with motor learning ability in a previously trained visuomotor task in humans. We further show that the associated functional subnetwork connectivity but not the global brain network properties are susceptible to ketamine. Our findings suggest a distinct functional role for learning-related global versus local network metrics and support the idea of a preferential susceptibility of learning-associated subnetworks to -methyl- -aspartate antagonist and plasticity-related consolidation effects.
Graph theoretical functional magnetic resonance imaging (fMRI) studies have demonstrated that brain networks reorganize significantly during motor skill acquisition, yet the associations between motor learning ability, brain network features, and the underlying biological mechanisms remain unclear. In the current study, we applied a visually guided sequential pinch force learning task and graph theoretical analyses to investigate the associations between short-term motor learning ability and resting-state brain network metrics in 60 healthy subjects. We further probed the test-retest reliability ( n = 26) and potential effects of the N -methyl- d -aspartate (NMDA) antagonist ketamine ( n = 19) in independent healthy volunteers. Our results show that the improvement of motor performance after short-term training was positively correlated with small-worldness ( p = 0.032) and global efficiency ( p = 0.025), whereas negatively correlated with characteristic path length ( p = 0.014) and transitivity ( p = 0.025). In addition, using network-based statistics (NBS), we identified a learning ability–associated ( p = 0.037) and ketamine-susceptible ( p = 0.027) cerebellar-cortical network with fair to good reliability (intraclass correlation coefficient [ICC] > 0.7) and higher functional connectivity in better learners. Our results provide new evidence for the association of intrinsic brain network features with motor learning and suggest a role of NMDA-related glutamatergic processes in learning-associated subnetworks. Learning a new motor skill prompts immediate reconfigurations of distributed brain networks followed by adaptive changes in intrinsic brain circuits related to synaptic plasticity. Here, we identify global brain network properties and a cerebellar-cortical functional subnetwork that are both significantly associated with motor learning ability in a previously trained visuomotor task in humans. We further show that the associated functional subnetwork connectivity but not the global brain network properties are susceptible to ketamine. Our findings suggest a distinct functional role for learning-related global versus local network metrics and support the idea of a preferential susceptibility of learning-associated subnetworks to N -methyl- d -aspartate antagonist and plasticity-related consolidation effects.
Graph theoretical functional magnetic resonance imaging (fMRI) studies have demonstrated that brain networks reorganize significantly during motor skill acquisition, yet the associations between motor learning ability, brain network features, and the underlying biological mechanisms remain unclear. In the current study, we applied a visually guided sequential pinch force learning task and graph theoretical analyses to investigate the associations between short-term motor learning ability and resting-state brain network metrics in 60 healthy subjects. We further probed the test-retest reliability (n = 26) and potential effects of the N-methyl-d-aspartate (NMDA) antagonist ketamine (n = 19) in independent healthy volunteers. Our results show that the improvement of motor performance after short-term training was positively correlated with small-worldness (p = 0.032) and global efficiency (p = 0.025), whereas negatively correlated with characteristic path length (p = 0.014) and transitivity (p = 0.025). In addition, using network-based statistics (NBS), we identified a learning ability–associated (p = 0.037) and ketamine-susceptible (p = 0.027) cerebellar-cortical network with fair to good reliability (intraclass correlation coefficient [ICC] > 0.7) and higher functional connectivity in better learners. Our results provide new evidence for the association of intrinsic brain network features with motor learning and suggest a role of NMDA-related glutamatergic processes in learning-associated subnetworks.Author Summary: Learning a new motor skill prompts immediate reconfigurations of distributed brain networks followed by adaptive changes in intrinsic brain circuits related to synaptic plasticity. Here, we identify global brain network properties and a cerebellar-cortical functional subnetwork that are both significantly associated with motor learning ability in a previously trained visuomotor task in humans. We further show that the associated functional subnetwork connectivity but not the global brain network properties are susceptible to ketamine. Our findings suggest a distinct functional role for learning-related global versus local network metrics and support the idea of a preferential susceptibility of learning-associated subnetworks to N-methyl-d-aspartate antagonist and plasticity-related consolidation effects.
Graph theoretical functional magnetic resonance imaging (fMRI) studies have demonstrated that brain networks reorganize significantly during motor skill acquisition, yet the associations between motor learning ability, brain network features, and the underlying biological mechanisms remain unclear. In the current study, we applied a visually guided sequential pinch force learning task and graph theoretical analyses to investigate the associations between short-term motor learning ability and resting-state brain network metrics in 60 healthy subjects. We further probed the test-retest reliability ( = 26) and potential effects of the -methyl-d-aspartate (NMDA) antagonist ketamine ( = 19) in independent healthy volunteers. Our results show that the improvement of motor performance after short-term training was positively correlated with small-worldness ( = 0.032) and global efficiency ( = 0.025), whereas negatively correlated with characteristic path length ( = 0.014) and transitivity ( = 0.025). In addition, using network-based statistics (NBS), we identified a learning ability-associated ( = 0.037) and ketamine-susceptible ( = 0.027) cerebellar-cortical network with fair to good reliability (intraclass correlation coefficient [ICC] > 0.7) and higher functional connectivity in better learners. Our results provide new evidence for the association of intrinsic brain network features with motor learning and suggest a role of NMDA-related glutamatergic processes in learning-associated subnetworks.
Graph theoretical functional magnetic resonance imaging (fMRI) studies have demonstrated that brain networks reorganize significantly during motor skill acquisition, yet the associations between motor learning ability, brain network features, and the underlying biological mechanisms remain unclear. In the current study, we applied a visually guided sequential pinch force learning task and graph theoretical analyses to investigate the associations between short-term motor learning ability and resting-state brain network metrics in 60 healthy subjects. We further probed the test-retest reliability ( n = 26) and potential effects of the N-methyl-d-aspartate (NMDA) antagonist ketamine ( n = 19) in independent healthy volunteers. Our results show that the improvement of motor performance after short-term training was positively correlated with small-worldness ( p = 0.032) and global efficiency ( p = 0.025), whereas negatively correlated with characteristic path length ( p = 0.014) and transitivity ( p = 0.025). In addition, using network-based statistics (NBS), we identified a learning ability–associated ( p = 0.037) and ketamine-susceptible ( p = 0.027) cerebellar-cortical network with fair to good reliability (intraclass correlation coefficient [ICC] > 0.7) and higher functional connectivity in better learners. Our results provide new evidence for the association of intrinsic brain network features with motor learning and suggest a role of NMDA-related glutamatergic processes in learning-associated subnetworks. Author Summary Learning a new motor skill prompts immediate reconfigurations of distributed brain networks followed by adaptive changes in intrinsic brain circuits related to synaptic plasticity. Here, we identify global brain network properties and a cerebellar-cortical functional subnetwork that are both significantly associated with motor learning ability in a previously trained visuomotor task in humans. We further show that the associated functional subnetwork connectivity but not the global brain network properties are susceptible to ketamine. Our findings suggest a distinct functional role for learning-related global versus local network metrics and support the idea of a preferential susceptibility of learning-associated subnetworks to N-methyl-d-aspartate antagonist and plasticity-related consolidation effects.
Author Meyer-Lindenberg, Andreas
Schäfer, Axel
Geiger, Lena S.
Schwarz, Emanuel
Tost, Heike
Moessnang, Carolin
Schweiger, Janina I.
Dixson, Luanna
Ruf, Matthias
Reis, Janine
Zang, Zhenxiang
Moscicki, Alexander
Braun, Urs
Zangl, Maria
Cao, Hengyi
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Cites_doi 10.1007/s002210050770
10.1016/j.neuroimage.2017.02.005
10.1016/j.cortex.2012.05.022
10.1371/journal.pone.0068910
10.3389/fnhum.2013.00166
10.1016/j.neuron.2011.10.008
10.1093/cercor/bhp189
10.1038/sj.npp.1300317
10.1073/pnas.0601602103
10.1016/j.cub.2009.04.028
10.1016/j.neuroimage.2014.12.046
10.1002/hbm.22947
10.1016/j.neuroimage.2009.10.003
10.1038/nrn2575
10.1016/j.neuroimage.2010.06.041
10.1523/JNEUROSCI.4432-15.2016
10.3389/neuro.09.055.2009
10.1016/j.brainres.2013.04.021
10.1093/cercor/bhv018
10.1371/journal.pone.0006626
10.1016/j.neuroimage.2011.10.018
10.1073/pnas.022615199
10.1016/j.conb.2005.03.004
10.1152/jn.00943.2004
10.1016/j.neuroimage.2011.08.044
10.1097/ALN.0b013e31826a0db3
10.1093/biomet/75.4.800
10.1016/j.neuroimage.2012.03.067
10.1093/cercor/bhw134
10.1038/nn.4179
10.1073/pnas.1018985108
10.1007/s00213-015-4022-y
10.1016/S0959-4388(02)00307-0
10.1016/j.neuroimage.2012.08.052
10.1006/nimg.2001.0978
10.1371/journal.pone.0036052
10.1523/JNEUROSCI.1443-09.2009
10.1016/j.neuroimage.2009.12.027
10.1016/j.brainres.2015.01.016
10.1016/j.neuroimage.2012.11.020
10.1523/JNEUROSCI.1034-04.2004
10.1093/cercor/bhw286
10.1016/j.neuroimage.2013.03.004
10.1523/JNEUROSCI.2733-16.2016
10.1016/j.neuroimage.2014.01.026
10.1038/npp.2015.291
10.1038/nn.3993
10.1016/j.neuron.2010.03.035
10.1523/JNEUROSCI.4341-13.2014
10.1006/brcg.2000.1237
10.1016/j.bbr.2011.09.044
10.1016/j.tics.2017.01.010
10.1016/j.biopsych.2012.03.026
10.1016/j.neuroimage.2013.09.013
10.1007/s12264-012-1254-2
10.1073/pnas.0805413106
10.1523/JNEUROSCI.16-20-06364.1996
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Issue 4
Keywords Resting-state fMRI
System neuroscience
Functional brain networks
Short-term motor learning
NMDA receptor-related plasticity
Language English
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References bib36
bib37
bib34
bib35
bib32
bib33
bib30
bib31
bib29
bib40
bib47
bib48
bib45
bib46
bib43
bib44
bib41
bib42
bib9
bib7
bib8
bib5
bib6
bib3
bib38
bib4
bib39
bib1
bib2
Yan C. (bib58) 2010; 4
Wang J. (bib55) 2010; 4
bib50
bib51
bib14
bib59
bib12
bib56
bib13
bib57
bib10
bib54
bib11
Kraguljac N. V. (bib27) 2016
Kuang S. (bib28) 2016; 26
bib52
bib53
Fleiss J. L. (bib15) 1986
bib49
bib61
bib60
bib25
bib26
bib23
bib24
bib21
bib22
bib63
bib20
bib18
bib19
bib16
bib17
References_xml – ident: bib48
  doi: 10.1007/s002210050770
– ident: bib50
  doi: 10.1016/j.neuroimage.2017.02.005
– volume-title: The Design and Analysis of Clinical Experiments
  year: 1986
  ident: bib15
  contributor:
    fullname: Fleiss J. L.
– year: 2016
  ident: bib27
  publication-title: Molecular Psychiatry
  contributor:
    fullname: Kraguljac N. V.
– ident: bib3
  doi: 10.1016/j.cortex.2012.05.022
– ident: bib57
  doi: 10.1371/journal.pone.0068910
– ident: bib43
  doi: 10.3389/fnhum.2013.00166
– ident: bib11
  doi: 10.1016/j.neuron.2011.10.008
– ident: bib33
  doi: 10.1093/cercor/bhp189
– ident: bib20
  doi: 10.1038/sj.npp.1300317
– ident: bib35
  doi: 10.1073/pnas.0601602103
– ident: bib2
  doi: 10.1016/j.cub.2009.04.028
– ident: bib1
  doi: 10.1016/j.neuroimage.2014.12.046
– ident: bib34
  doi: 10.1002/hbm.22947
– volume: 4
  start-page: 13
  year: 2010
  ident: bib58
  publication-title: Frontiers in Systems Neuroscience
  contributor:
    fullname: Yan C.
– ident: bib42
  doi: 10.1016/j.neuroimage.2009.10.003
– ident: bib9
  doi: 10.1038/nrn2575
– ident: bib60
  doi: 10.1016/j.neuroimage.2010.06.041
– ident: bib18
  doi: 10.1523/JNEUROSCI.4432-15.2016
– ident: bib47
  doi: 10.3389/neuro.09.055.2009
– ident: bib25
  doi: 10.1016/j.brainres.2013.04.021
– ident: bib52
  doi: 10.1093/cercor/bhv018
– ident: bib4
  doi: 10.1371/journal.pone.0006626
– ident: bib39
  doi: 10.1016/j.neuroimage.2011.10.018
– ident: bib14
  doi: 10.1073/pnas.022615199
– ident: bib13
  doi: 10.1016/j.conb.2005.03.004
– ident: bib46
  doi: 10.1152/jn.00943.2004
– ident: bib8
  doi: 10.1016/j.neuroimage.2011.08.044
– ident: bib36
  doi: 10.1097/ALN.0b013e31826a0db3
– ident: bib24
  doi: 10.1093/biomet/75.4.800
– ident: bib22
  doi: 10.1016/j.neuroimage.2012.03.067
– ident: bib26
  doi: 10.1093/cercor/bhw134
– ident: bib41
  doi: 10.1038/nn.4179
– ident: bib6
  doi: 10.1073/pnas.1018985108
– ident: bib19
  doi: 10.1007/s00213-015-4022-y
– ident: bib23
  doi: 10.1016/S0959-4388(02)00307-0
– ident: bib45
  doi: 10.1016/j.neuroimage.2012.08.052
– ident: bib49
  doi: 10.1006/nimg.2001.0978
– ident: bib63
  doi: 10.1371/journal.pone.0036052
– ident: bib51
  doi: 10.1523/JNEUROSCI.1443-09.2009
– volume: 4
  start-page: 16
  year: 2010
  ident: bib55
  publication-title: Frontiers in Systems Neuroscience
  contributor:
    fullname: Wang J.
– ident: bib61
  doi: 10.1016/j.neuroimage.2009.12.027
– ident: bib53
  doi: 10.1016/j.brainres.2015.01.016
– ident: bib21
  doi: 10.1016/j.neuroimage.2012.11.020
– ident: bib30
  doi: 10.1523/JNEUROSCI.1034-04.2004
– ident: bib31
  doi: 10.1093/cercor/bhw286
– volume: 26
  start-page: 731
  issue: 2
  year: 2016
  ident: bib28
  publication-title: Cerebral Cortex
  contributor:
    fullname: Kuang S.
– ident: bib59
  doi: 10.1016/j.neuroimage.2013.03.004
– ident: bib32
  doi: 10.1523/JNEUROSCI.2733-16.2016
– ident: bib56
  doi: 10.1016/j.neuroimage.2014.01.026
– ident: bib16
  doi: 10.1038/npp.2015.291
– ident: bib7
  doi: 10.1038/nn.3993
– ident: bib17
  doi: 10.1016/j.neuron.2010.03.035
– ident: bib44
  doi: 10.1523/JNEUROSCI.4341-13.2014
– ident: bib29
  doi: 10.1006/brcg.2000.1237
– ident: bib38
  doi: 10.1016/j.bbr.2011.09.044
– ident: bib5
  doi: 10.1016/j.tics.2017.01.010
– ident: bib54
  doi: 10.1016/j.biopsych.2012.03.026
– ident: bib10
  doi: 10.1016/j.neuroimage.2013.09.013
– ident: bib12
  doi: 10.1007/s12264-012-1254-2
– ident: bib40
  doi: 10.1073/pnas.0805413106
– ident: bib37
  doi: 10.1523/JNEUROSCI.16-20-06364.1996
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Snippet Graph theoretical functional magnetic resonance imaging (fMRI) studies have demonstrated that brain networks reorganize significantly during motor skill...
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SubjectTerms Brain
Brain mapping
Cerebellum
Cognitive tasks
Correlation coefficients
Functional brain networks
Functional magnetic resonance imaging
Glutamatergic transmission
Glutamic acid receptors
Glutamic acid receptors (ionotropic)
Ketamine
Learning
Magnetic resonance imaging
Motor skill
Motor skill learning
Motor task performance
N-Methyl-D-aspartic acid receptors
Neural networks
Neuroimaging
NMDA receptor-related plasticity
Pinch force
Reliability
Resting-state fMRI
Sensorimotor integration
Short-term motor learning
Synaptic plasticity
System neuroscience
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Title Resting-state brain network features associated with short-term skill learning ability in humans and the influence of N -methyl- d -aspartate receptor antagonism
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