Resting network is composed of more than one neural pattern: An fMRI study

Tien-Wen Lee, Georg Franz Josef Northoff, Y.-T. Wu

Research output: Contribution to journalArticle

14 Citations (Scopus)

Abstract

In resting state, the dynamics of blood oxygen level-dependent signals recorded by functional magnetic resonance imaging (fMRI) showed reliable modular structures. To explore the network property, previous research used to construct an adjacency matrix by Pearson's correlation and prune it using stringent statistical threshold. However, traditional analyses may lose useful information at middle to moderate high correlation level. This resting fMRI study adopted full connection as a criterion to partition the adjacency matrix into composite sub-matrices (neural patterns) and investigated the associated community organization and network features. Modular consistency across subjects was assessed using scaled inclusivity index. Our results disclosed two neural patterns with reliable modular structures. Concordant with the results of traditional intervention, community detection analysis showed that neural pattern 1, the sub-matrix at highest correlation level, was composed of sensory-motor, visual associative, default mode/midline, temporal limbic and basal ganglia structures. The neural pattern 2 was situated at middle to moderate high correlation level and comprised two larger modules, possibly associated with mental processing of outer world (such as visuo-associative, auditory and sensory-motor networks) and inner homeostasis (such as default-mode, midline and limbic systems). Graph theoretical analyses further demonstrated that the network feature of neural pattern 1 was more local and segregate, whereas that of neural pattern 2 was more global and integrative. Our results suggest that future resting fMRI research may take the neural pattern at middle to moderate high correlation range into consideration, which has long been ignored in extant literature. The variation of neural pattern 2 could be relevant to individual characteristics of self-regulatory functions, and the disruption in its topology may underlie the pathology of several neuropsychiatric illnesses. © 2014 IBRO.
Original languageEnglish
Pages (from-to)198-208
Number of pages11
JournalNeuroscience
Volume274
DOIs
Publication statusPublished - 2014
Externally publishedYes

Fingerprint

Magnetic Resonance Imaging
Community Networks
Limbic System
Basal Ganglia
Research
Homeostasis
Organizations
Pathology
Oxygen

Keywords

  • Community detection
  • Functional connectivity
  • Functional magnetic resonance imaging (fMRI)
  • Graph theory
  • Resting fMRI
  • Scaled inclusivity
  • adult
  • article
  • association cortex
  • auditory cortex
  • basal ganglion
  • BOLD signal
  • brain function
  • brain region
  • functional magnetic resonance imaging
  • human
  • human experiment
  • limbic cortex
  • normal human
  • nuclear magnetic resonance scanner
  • priority journal
  • resting state network
  • sensorimotor cortex
  • biological model
  • brain
  • brain mapping
  • female
  • image processing
  • male
  • nerve cell network
  • nuclear magnetic resonance imaging
  • physiology
  • procedures
  • statistical analysis
  • young adult
  • Adult
  • Brain
  • Brain Mapping
  • Data Interpretation, Statistical
  • Female
  • Humans
  • Image Processing, Computer-Assisted
  • Magnetic Resonance Imaging
  • Male
  • Models, Neurological
  • Nerve Net
  • Young Adult

Cite this

Resting network is composed of more than one neural pattern: An fMRI study. / Lee, Tien-Wen; Northoff, Georg Franz Josef; Wu, Y.-T.

In: Neuroscience, Vol. 274, 2014, p. 198-208.

Research output: Contribution to journalArticle

@article{a6565bf2177a498ba854a6448b019181,
title = "Resting network is composed of more than one neural pattern: An fMRI study",
abstract = "In resting state, the dynamics of blood oxygen level-dependent signals recorded by functional magnetic resonance imaging (fMRI) showed reliable modular structures. To explore the network property, previous research used to construct an adjacency matrix by Pearson's correlation and prune it using stringent statistical threshold. However, traditional analyses may lose useful information at middle to moderate high correlation level. This resting fMRI study adopted full connection as a criterion to partition the adjacency matrix into composite sub-matrices (neural patterns) and investigated the associated community organization and network features. Modular consistency across subjects was assessed using scaled inclusivity index. Our results disclosed two neural patterns with reliable modular structures. Concordant with the results of traditional intervention, community detection analysis showed that neural pattern 1, the sub-matrix at highest correlation level, was composed of sensory-motor, visual associative, default mode/midline, temporal limbic and basal ganglia structures. The neural pattern 2 was situated at middle to moderate high correlation level and comprised two larger modules, possibly associated with mental processing of outer world (such as visuo-associative, auditory and sensory-motor networks) and inner homeostasis (such as default-mode, midline and limbic systems). Graph theoretical analyses further demonstrated that the network feature of neural pattern 1 was more local and segregate, whereas that of neural pattern 2 was more global and integrative. Our results suggest that future resting fMRI research may take the neural pattern at middle to moderate high correlation range into consideration, which has long been ignored in extant literature. The variation of neural pattern 2 could be relevant to individual characteristics of self-regulatory functions, and the disruption in its topology may underlie the pathology of several neuropsychiatric illnesses. {\circledC} 2014 IBRO.",
keywords = "Community detection, Functional connectivity, Functional magnetic resonance imaging (fMRI), Graph theory, Resting fMRI, Scaled inclusivity, adult, article, association cortex, auditory cortex, basal ganglion, BOLD signal, brain function, brain region, functional magnetic resonance imaging, human, human experiment, limbic cortex, normal human, nuclear magnetic resonance scanner, priority journal, resting state network, sensorimotor cortex, biological model, brain, brain mapping, female, image processing, male, nerve cell network, nuclear magnetic resonance imaging, physiology, procedures, statistical analysis, young adult, Adult, Brain, Brain Mapping, Data Interpretation, Statistical, Female, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Models, Neurological, Nerve Net, Young Adult",
author = "Tien-Wen Lee and Northoff, {Georg Franz Josef} and Y.-T. Wu",
note = "Export Date: 11 May 2016 CODEN: NRSCD Correspondence Address: Lee, T.-W.; Dajia Lee's General Hospital, Lee's Medical Corporation, Department of Psychiatry, No. 2, Bade Street, Dajia District, Taichung City 437, Taiwan; email: dwlee_ibru@yahoo.com.tw Tradenames: Tesla scanner, General Electric, United States Manufacturers: General Electric, United States References: Bassett, D.S., Wymbs, N.F., Porter, M.A., Mucha, P.J., Carlson, J.M., Grafton, S.T., Dynamic reconfiguration of human brain networks during learning (2011) Proc Natl Acad Sci U S A, 108, pp. 7641-7646; Eickhoff, S.B., Stephan, K.E., Mohlberg, H., Grefkes, C., Fink, G.R., Amunts, K., Zilles, K., A new SPM toolbox for combining probabilistic cytoarchitectonic maps and functional imaging data (2005) Neuroimage, 25, pp. 1325-1335; Fransson, P., Spontaneous low-frequency BOLD signal fluctuations: an fMRI investigation of the resting-state default mode of brain function hypothesis (2005) Hum Brain Mapp, 26, pp. 15-29; Frey, U., Frey, S., Schollmeier, F., Krug, M., Influence of actinomycin D, a RNA synthesis inhibitor, on long-term potentiation in rat hippocampal neurons in vivo and in vitro (1996) J Physiol, 490 (PART 3), pp. 703-711; Friston, K.J., Modalities, modes, and models in functional neuroimaging (2009) Science, 326, pp. 399-403; Goldman-Rakic, P.S., The prefrontal landscape: implications of functional architecture for understanding human mentation and the central executive (1996) Philos Trans R Soc Lond B Biol Sci, 351, pp. 1445-1453; Good, B.H., de Montjoye, Y.A., Clauset, A., Performance of modularity maximization in practical contexts (2010) Phys Rev E, 81, p. 046106; Gray, J.R., Braver, T.S., Raichle, M.E., Integration of emotion and cognition in the lateral prefrontal cortex (2002) Proc Natl Acad Sci U S A, 99, pp. 4115-4120; Gusnard, D.A., Raichle, M.E., Searching for a baseline: functional imaging and the resting human brain (2001) Nat Rev Neurosci, 2, pp. 685-694; He, B.J., Spontaneous and task-evoked brain activity negatively interact (2013) J Neurosci, 33, pp. 4672-4682; He, Y., Wang, J., Wang, L., Chen, Z.J., Yan, C., Yang, H., Tang, H., Evans, A.C., Uncovering intrinsic modular organization of spontaneous brain activity in humans (2009) PLoS ONE, 4, pp. e5226; Jo, H.J., Saad, Z.S., Simmons, W.K., Milbury, L.A., Cox, R.W., Mapping sources of correlation in resting state FMRI, with artifact detection and removal (2010) Neuroimage, 52, pp. 571-582; Karnath, H.O., New insights into the functions of the superior temporal cortex (2001) Nat Rev Neurosci, 2, pp. 568-576; Kriegeskorte, N., Simmons, W.K., Bellgowan, P.S., Baker, C.I., Circular analysis in systems neuroscience: the dangers of double dipping (2009) Nat Neurosci, 12, pp. 535-540; Kringelbach, M.L., Rolls, E.T., The functional neuroanatomy of the human orbitofrontal cortex: evidence from neuroimaging and neuropsychology (2004) Prog Neurobiol, 72, pp. 341-372; Lancichinetti, A., Radicchi, F., Ramasco, J.J., Fortunato, S., Finding statistically significant communities in networks (2011) PLoS ONE, 6, pp. e18961; Langer, N., Pedroni, A., Jancke, L., The problem of thresholding in small-world network analysis (2013) PLoS ONE, 8, pp. e53199; Leicht, E.A., Newman, M.E., Community structure in directed networks (2008) Phys Rev Lett, 100, p. 118703; Logothetis, N.K., Pauls, J., Augath, M., Trinath, T., Oeltermann, A., Neurophysiological investigation of the basis of the fMRI signal (2001) Nature, 412, pp. 150-157; Lu, H., Zou, Q., Gu, H., Raichle, M.E., Stein, E.A., Yang, Y., Rat brains also have a default mode network (2012) Proc Natl Acad Sci U S A, 109, pp. 3979-3984; Mitchell, J.P., Heatherton, T.F., Macrae, C.N., Distinct neural systems subserve person and object knowledge (2002) Proc Natl Acad Sci U S A, 99, pp. 15238-15243; Moussa, M.N., Steen, M.R., Laurienti, P.J., Hayasaka, S., Consistency of network modules in resting-state FMRI connectome data (2012) PLoS ONE, 7, pp. e44428; Northoff, G., Bermpohl, F., Cortical midline structures and the self (2004) Trends Cogn Sci, 8, pp. 102-107; Northoff, G., Qin, P., Feinberg, T.E., Brain imaging of the self-conceptual, anatomical and methodological issues (2011) Conscious Cogn, 20, pp. 52-63; Olejarczyk, E., Application of fractal dimension method of functional MRI time-series to limbic dysregulation in anxiety study (2007) Conf Proc IEEE Eng Med Biol Soc, 2007, pp. 3408-3410; Ongur, D., Price, J.L., The organization of networks within the orbital and medial prefrontal cortex of rats, monkeys and humans (2000) Cereb Cortex, 10, pp. 206-219; Rubinov, M., Sporns, O., Complex network measures of brain connectivity: uses and interpretations (2010) Neuroimage, 52, pp. 1059-1069; Schneider, F., Bermpohl, F., Heinzel, A., Rotte, M., Walter, M., Tempelmann, C., Wiebking, C., Northoff, G., The resting brain and our self: self-relatedness modulates resting state neural activity in cortical midline structures (2008) Neuroscience, 157, pp. 120-131; Schwarz, A.J., Gozzi, A., Bifone, A., Community structure and modularity in networks of correlated brain activity (2008) Magn Reson Imaging, 26, pp. 914-920; Shen, X., Liu, H., Hu, Z., Hu, H., Shi, P., The relationship between cerebral glucose metabolism and age: report of a large brain PET data set (2012) PLoS ONE, 7, pp. e51517; Shin, J., Tsui, W., Li, Y., Lee, S.Y., Kim, S.J., Cho, S.J., Kim, Y.B., de Leon, M.J., Resting-state glucose metabolism level is associated with the regional pattern of amyloid pathology in Alzheimer's disease (2011) Int J Alzheimer Dis, 2011, p. 759780; Sokoloff, L., Mangold, R., Wechsler, R.L., Kenney, C., Kety, S.S., The effect of mental arithmetic on cerebral circulation and metabolism (1955) J Clin Invest, 34, pp. 1101-1108; Steen, M., Hayasaka, S., Joyce, K., Laurienti, P., Assessing the consistency of community structure in complex networks (2011) Phys Rev E, 84, p. 016111; Tarjan, R., Depth-first search and linear graph algorithms (1972) SIAM J Comput, 1, pp. 146-160; Tomasi, D., Volkow, N.D., Functional connectivity hubs in the human brain (2011) Neuroimage, 57, pp. 908-917; Vul, E., Harris, C., Winkielman, P., Pashler, H., Puzzlingly high correlations in fMRI studies of emotion, personality, and social cognition (2009) Perspect Psychol Sci, 4, pp. 274-290",
year = "2014",
doi = "10.1016/j.neuroscience.2014.05.035",
language = "English",
volume = "274",
pages = "198--208",
journal = "Neuroscience",
issn = "0306-4522",
publisher = "Elsevier Ireland Ltd",

}

TY - JOUR

T1 - Resting network is composed of more than one neural pattern: An fMRI study

AU - Lee, Tien-Wen

AU - Northoff, Georg Franz Josef

AU - Wu, Y.-T.

N1 - Export Date: 11 May 2016 CODEN: NRSCD Correspondence Address: Lee, T.-W.; Dajia Lee's General Hospital, Lee's Medical Corporation, Department of Psychiatry, No. 2, Bade Street, Dajia District, Taichung City 437, Taiwan; email: dwlee_ibru@yahoo.com.tw Tradenames: Tesla scanner, General Electric, United States Manufacturers: General Electric, United States References: Bassett, D.S., Wymbs, N.F., Porter, M.A., Mucha, P.J., Carlson, J.M., Grafton, S.T., Dynamic reconfiguration of human brain networks during learning (2011) Proc Natl Acad Sci U S A, 108, pp. 7641-7646; Eickhoff, S.B., Stephan, K.E., Mohlberg, H., Grefkes, C., Fink, G.R., Amunts, K., Zilles, K., A new SPM toolbox for combining probabilistic cytoarchitectonic maps and functional imaging data (2005) Neuroimage, 25, pp. 1325-1335; Fransson, P., Spontaneous low-frequency BOLD signal fluctuations: an fMRI investigation of the resting-state default mode of brain function hypothesis (2005) Hum Brain Mapp, 26, pp. 15-29; Frey, U., Frey, S., Schollmeier, F., Krug, M., Influence of actinomycin D, a RNA synthesis inhibitor, on long-term potentiation in rat hippocampal neurons in vivo and in vitro (1996) J Physiol, 490 (PART 3), pp. 703-711; Friston, K.J., Modalities, modes, and models in functional neuroimaging (2009) Science, 326, pp. 399-403; Goldman-Rakic, P.S., The prefrontal landscape: implications of functional architecture for understanding human mentation and the central executive (1996) Philos Trans R Soc Lond B Biol Sci, 351, pp. 1445-1453; Good, B.H., de Montjoye, Y.A., Clauset, A., Performance of modularity maximization in practical contexts (2010) Phys Rev E, 81, p. 046106; Gray, J.R., Braver, T.S., Raichle, M.E., Integration of emotion and cognition in the lateral prefrontal cortex (2002) Proc Natl Acad Sci U S A, 99, pp. 4115-4120; Gusnard, D.A., Raichle, M.E., Searching for a baseline: functional imaging and the resting human brain (2001) Nat Rev Neurosci, 2, pp. 685-694; He, B.J., Spontaneous and task-evoked brain activity negatively interact (2013) J Neurosci, 33, pp. 4672-4682; He, Y., Wang, J., Wang, L., Chen, Z.J., Yan, C., Yang, H., Tang, H., Evans, A.C., Uncovering intrinsic modular organization of spontaneous brain activity in humans (2009) PLoS ONE, 4, pp. e5226; Jo, H.J., Saad, Z.S., Simmons, W.K., Milbury, L.A., Cox, R.W., Mapping sources of correlation in resting state FMRI, with artifact detection and removal (2010) Neuroimage, 52, pp. 571-582; Karnath, H.O., New insights into the functions of the superior temporal cortex (2001) Nat Rev Neurosci, 2, pp. 568-576; Kriegeskorte, N., Simmons, W.K., Bellgowan, P.S., Baker, C.I., Circular analysis in systems neuroscience: the dangers of double dipping (2009) Nat Neurosci, 12, pp. 535-540; Kringelbach, M.L., Rolls, E.T., The functional neuroanatomy of the human orbitofrontal cortex: evidence from neuroimaging and neuropsychology (2004) Prog Neurobiol, 72, pp. 341-372; Lancichinetti, A., Radicchi, F., Ramasco, J.J., Fortunato, S., Finding statistically significant communities in networks (2011) PLoS ONE, 6, pp. e18961; Langer, N., Pedroni, A., Jancke, L., The problem of thresholding in small-world network analysis (2013) PLoS ONE, 8, pp. e53199; Leicht, E.A., Newman, M.E., Community structure in directed networks (2008) Phys Rev Lett, 100, p. 118703; Logothetis, N.K., Pauls, J., Augath, M., Trinath, T., Oeltermann, A., Neurophysiological investigation of the basis of the fMRI signal (2001) Nature, 412, pp. 150-157; Lu, H., Zou, Q., Gu, H., Raichle, M.E., Stein, E.A., Yang, Y., Rat brains also have a default mode network (2012) Proc Natl Acad Sci U S A, 109, pp. 3979-3984; Mitchell, J.P., Heatherton, T.F., Macrae, C.N., Distinct neural systems subserve person and object knowledge (2002) Proc Natl Acad Sci U S A, 99, pp. 15238-15243; Moussa, M.N., Steen, M.R., Laurienti, P.J., Hayasaka, S., Consistency of network modules in resting-state FMRI connectome data (2012) PLoS ONE, 7, pp. e44428; Northoff, G., Bermpohl, F., Cortical midline structures and the self (2004) Trends Cogn Sci, 8, pp. 102-107; Northoff, G., Qin, P., Feinberg, T.E., Brain imaging of the self-conceptual, anatomical and methodological issues (2011) Conscious Cogn, 20, pp. 52-63; Olejarczyk, E., Application of fractal dimension method of functional MRI time-series to limbic dysregulation in anxiety study (2007) Conf Proc IEEE Eng Med Biol Soc, 2007, pp. 3408-3410; Ongur, D., Price, J.L., The organization of networks within the orbital and medial prefrontal cortex of rats, monkeys and humans (2000) Cereb Cortex, 10, pp. 206-219; Rubinov, M., Sporns, O., Complex network measures of brain connectivity: uses and interpretations (2010) Neuroimage, 52, pp. 1059-1069; Schneider, F., Bermpohl, F., Heinzel, A., Rotte, M., Walter, M., Tempelmann, C., Wiebking, C., Northoff, G., The resting brain and our self: self-relatedness modulates resting state neural activity in cortical midline structures (2008) Neuroscience, 157, pp. 120-131; Schwarz, A.J., Gozzi, A., Bifone, A., Community structure and modularity in networks of correlated brain activity (2008) Magn Reson Imaging, 26, pp. 914-920; Shen, X., Liu, H., Hu, Z., Hu, H., Shi, P., The relationship between cerebral glucose metabolism and age: report of a large brain PET data set (2012) PLoS ONE, 7, pp. e51517; Shin, J., Tsui, W., Li, Y., Lee, S.Y., Kim, S.J., Cho, S.J., Kim, Y.B., de Leon, M.J., Resting-state glucose metabolism level is associated with the regional pattern of amyloid pathology in Alzheimer's disease (2011) Int J Alzheimer Dis, 2011, p. 759780; Sokoloff, L., Mangold, R., Wechsler, R.L., Kenney, C., Kety, S.S., The effect of mental arithmetic on cerebral circulation and metabolism (1955) J Clin Invest, 34, pp. 1101-1108; Steen, M., Hayasaka, S., Joyce, K., Laurienti, P., Assessing the consistency of community structure in complex networks (2011) Phys Rev E, 84, p. 016111; Tarjan, R., Depth-first search and linear graph algorithms (1972) SIAM J Comput, 1, pp. 146-160; Tomasi, D., Volkow, N.D., Functional connectivity hubs in the human brain (2011) Neuroimage, 57, pp. 908-917; Vul, E., Harris, C., Winkielman, P., Pashler, H., Puzzlingly high correlations in fMRI studies of emotion, personality, and social cognition (2009) Perspect Psychol Sci, 4, pp. 274-290

PY - 2014

Y1 - 2014

N2 - In resting state, the dynamics of blood oxygen level-dependent signals recorded by functional magnetic resonance imaging (fMRI) showed reliable modular structures. To explore the network property, previous research used to construct an adjacency matrix by Pearson's correlation and prune it using stringent statistical threshold. However, traditional analyses may lose useful information at middle to moderate high correlation level. This resting fMRI study adopted full connection as a criterion to partition the adjacency matrix into composite sub-matrices (neural patterns) and investigated the associated community organization and network features. Modular consistency across subjects was assessed using scaled inclusivity index. Our results disclosed two neural patterns with reliable modular structures. Concordant with the results of traditional intervention, community detection analysis showed that neural pattern 1, the sub-matrix at highest correlation level, was composed of sensory-motor, visual associative, default mode/midline, temporal limbic and basal ganglia structures. The neural pattern 2 was situated at middle to moderate high correlation level and comprised two larger modules, possibly associated with mental processing of outer world (such as visuo-associative, auditory and sensory-motor networks) and inner homeostasis (such as default-mode, midline and limbic systems). Graph theoretical analyses further demonstrated that the network feature of neural pattern 1 was more local and segregate, whereas that of neural pattern 2 was more global and integrative. Our results suggest that future resting fMRI research may take the neural pattern at middle to moderate high correlation range into consideration, which has long been ignored in extant literature. The variation of neural pattern 2 could be relevant to individual characteristics of self-regulatory functions, and the disruption in its topology may underlie the pathology of several neuropsychiatric illnesses. © 2014 IBRO.

AB - In resting state, the dynamics of blood oxygen level-dependent signals recorded by functional magnetic resonance imaging (fMRI) showed reliable modular structures. To explore the network property, previous research used to construct an adjacency matrix by Pearson's correlation and prune it using stringent statistical threshold. However, traditional analyses may lose useful information at middle to moderate high correlation level. This resting fMRI study adopted full connection as a criterion to partition the adjacency matrix into composite sub-matrices (neural patterns) and investigated the associated community organization and network features. Modular consistency across subjects was assessed using scaled inclusivity index. Our results disclosed two neural patterns with reliable modular structures. Concordant with the results of traditional intervention, community detection analysis showed that neural pattern 1, the sub-matrix at highest correlation level, was composed of sensory-motor, visual associative, default mode/midline, temporal limbic and basal ganglia structures. The neural pattern 2 was situated at middle to moderate high correlation level and comprised two larger modules, possibly associated with mental processing of outer world (such as visuo-associative, auditory and sensory-motor networks) and inner homeostasis (such as default-mode, midline and limbic systems). Graph theoretical analyses further demonstrated that the network feature of neural pattern 1 was more local and segregate, whereas that of neural pattern 2 was more global and integrative. Our results suggest that future resting fMRI research may take the neural pattern at middle to moderate high correlation range into consideration, which has long been ignored in extant literature. The variation of neural pattern 2 could be relevant to individual characteristics of self-regulatory functions, and the disruption in its topology may underlie the pathology of several neuropsychiatric illnesses. © 2014 IBRO.

KW - Community detection

KW - Functional connectivity

KW - Functional magnetic resonance imaging (fMRI)

KW - Graph theory

KW - Resting fMRI

KW - Scaled inclusivity

KW - adult

KW - article

KW - association cortex

KW - auditory cortex

KW - basal ganglion

KW - BOLD signal

KW - brain function

KW - brain region

KW - functional magnetic resonance imaging

KW - human

KW - human experiment

KW - limbic cortex

KW - normal human

KW - nuclear magnetic resonance scanner

KW - priority journal

KW - resting state network

KW - sensorimotor cortex

KW - biological model

KW - brain

KW - brain mapping

KW - female

KW - image processing

KW - male

KW - nerve cell network

KW - nuclear magnetic resonance imaging

KW - physiology

KW - procedures

KW - statistical analysis

KW - young adult

KW - Adult

KW - Brain

KW - Brain Mapping

KW - Data Interpretation, Statistical

KW - Female

KW - Humans

KW - Image Processing, Computer-Assisted

KW - Magnetic Resonance Imaging

KW - Male

KW - Models, Neurological

KW - Nerve Net

KW - Young Adult

U2 - 10.1016/j.neuroscience.2014.05.035

DO - 10.1016/j.neuroscience.2014.05.035

M3 - Article

VL - 274

SP - 198

EP - 208

JO - Neuroscience

JF - Neuroscience

SN - 0306-4522

ER -