Opinion
Expansion and Renormalization of Human Brain Structure During Skill Acquisition

https://doi.org/10.1016/j.tics.2017.09.008Get rights and content

Trends

Research on human plasticity has been energized by the discovery of experience-dependent growth of brain volume in adulthood. However, is it really feasible to portray the vast amount of knowledge and the large number of skills that humans acquire in terms of a perpetual process of brain volume growth?

Prominent theoretical accounts of plasticity, developmental data, and animal models suggest a sequence of learning-related expansion, selection, and renormalization of brain activity and structure.

Recent studies on experience-dependent changes in gray matter structure also support this model for human learning. Estimates of the volume of human primary motor cortices were recently shown to increase during the first weeks of motor learning and then partially renormalize during continued practice.

Research on human brain changes during skill acquisition has revealed brain volume expansion in task-relevant areas. However, the large number of skills that humans acquire during ontogeny militates against plasticity as a perpetual process of volume growth. Building on animal models and available theories, we promote the expansion–renormalization model for plastic changes in humans. The model predicts an initial increase of gray matter structure, potentially reflecting growth of neural resources like neurons, synapses, and glial cells, which is followed by a selection process operating on this new tissue leading to a complete or partial return to baseline of the overall volume after selection has ended. The model sheds new light on available evidence and current debates and fosters the search for mechanistic explanations.

Section snippets

Human Brain Plasticity: Expansion and Renormalization?

In 1894, Nobel Prize winner Santiago Ramón y Cajal, considered by many to be the father of modern neuroscience, proposed that mental activity might induce morphological changes in brain structure. Nearly 100 years later, studies using magnetic resonance imaging (MRI, see Glossary and Box 1) have reported experience-dependent increases in regional estimates of human brain volume and cortical thickness in adulthood. For example, it has been found that London taxi drivers’ gray matter in the

Expansion and Renormalization of Human Gray Matter Structure

Research has documented changes in human gray matter structure after a few months of training (e.g., 2, 5 as noted above) and has also indicated that such changes can emerge early during the learning process 7, 22, 23, 24. However, the fate and durability of these changes has not been tracked in the course of continuous learning in humans. Recently, we acquired up to 18 T1-weighted structural MR images over a 7-week period during which 15 right-handed adult participants practiced left-hand

Cellular Processes Potentially Underlying Gray Matter Changes

Increases and decreases of estimates of localized volume during learning as observed with MRI are most likely the result of a conglomerate of different cellular processes 14, 28. Figure 1 schematically illustrates these cellular processes. Several candidate mechanisms on the cellular and molecular level have been proposed that could account for MRI observations [14], including neurogenesis, synaptic changes, dendritic branching, and axon sprouting as well as changes in glial number and

Cortical Map Dynamics and Functional Changes

Similar to macroscopic changes in estimates of regional gray matter volume, cortical map plasticity follows a comparable pattern of expansion followed by renormalization during learning 16, 17, 18, 44, 45, 46, 47, 48, 49, 50. For example, it has been found that rats training to perform a skilled reaching task exhibit expanded cortical maps after 3 days of training [16]. After 8 days of training, however, these expansions had subsided, while behavioral performance remained stable. A similar

Formation and Elimination of Synapses

Research regarding learning-related changes in dendritic spines is consistent with the hypothesis that the memory trace serving skilled performance is often localized in rewired specific circuitry rather than in any large-scale expansion of tissue in the whole region 11, 36, 53. During motor skill acquisition or new sensory experiences, novel dendritic spines rapidly grow to form synapses in the sensory and motor cortices of rodents 19, 20, 21. In this process the dendrites are not merely

Plastic Changes: A Darwinian Learning Process

The pruning model of early development 56, 57, 58 posits the same general pattern of increase followed by decrease as described above, only on an ontogenetic timescale. The rapid increase of synapses after birth is followed by experience-dependent selective stabilization of behaviorally relevant connections and the elimination of those connections that prove to be non-functional [59], resulting in an overall trajectory of decrease from childhood to adolescence 60, 61 (but see also [62] for

Concluding Remarks and Future Perspectives

We have argued that the concepts of expansion, selection, and renormalization are consistent with animal models and theoretical accounts of skill acquisition and development and together contribute to a mechanistic understanding of human plasticity. Importantly, the expansion–renormalization model opens up several new research directions, informs predictions for work on experience-dependent and developmental changes in human brain structure (see Outstanding Questions), and calls for a critical

Acknowledgments

The authors thank Simone Kühn and Benjamín Garzón for valuable discussions, Ludmila Müller for rendering the figure, and Julia Delius und Lana Riccius for comments on the text. The work by M.L. on the manuscript was done in the context of research supported by the European Research Council under the EU’s Seventh Framework Programme (FP7/2007-2013)/ERC Grant Agreement N° 617280–REBOOT and the Swedish Research Council (446-2013-7189). Work by U.L. profited from a research stay as a Fernand

Glossary

Cortical maps
the cortical organization of sensory and motor systems is often described in terms of maps. Cortical maps are collections (areas) of minicolumns in the cortex whose functional topography corresponds to graded variations on an underlying sensory or motor dimension. In the somatotopic map of the motor cortex, for example, stimulation of different areas evokes movement of distinct parts of the body. These cortical representations are not static. Cortical map expansion refers to the

References (100)

  • O. Granert

    Manual activity shapes structure and function in contralateral human motor hand area

    Neuroimage

    (2011)
  • B. Draganski

    Decrease of thalamic gray matter following limb amputation

    Neuroimage

    (2006)
  • A. Ernst

    Neurogenesis in the striatum of the adult human brain

    Cell

    (2014)
  • J.A. Kleim

    Motor learning-dependent synaptogenesis is localized to functionally reorganized motor cortex

    Neurobiol. Learn. Mem.

    (2002)
  • A. Holtmaat

    Imaging of experience-dependent structural plasticity in the mouse neocortex in vivo

    Behav. Brain Res.

    (2008)
  • B. Kolb

    Contrasting effects of motor and visual spatial learning tasks on dendritic arborization and spine density in rats

    Neurobiol. Learn. Mem.

    (2008)
  • A.M. Sirevaag et al.

    Plasticity of GFAP-immunoreactive astrocyte size and number in visual cortex of rats reared in complex environments

    Brain Res.

    (1991)
  • Y. Yotsumoto

    Different dynamics of performance and brain activation in the time course of perceptual learning

    Neuron

    (2008)
  • L. Ma

    Changes in regional activity are accompanied with changes in inter-regional connectivity during 4 weeks motor learning

    Brain Res.

    (2010)
  • H. Takahashi

    Progressive plasticity of auditory cortex during appetitive operant conditioning

    Biosystems

    (2010)
  • D.T. Pruitt

    Forelimb training drives transient map reorganization in ipsilateral motor cortex

    Behav. Brain Res.

    (2016)
  • P. Caroni

    Synapse rearrangements upon learning: from divergent-sparse connectivity to dedicated sub-circuits

    Trends Neurosci.

    (2014)
  • P.R. Huttenlocher

    Morphometric study of human cerebral cortex development

    Neuropsychologia

    (1990)
  • D.D.M. O’Leary

    Development of connectional diversity and specificity in the mammalian brain by the pruning of collateral projections

    Curr. Opin. Neurobiol.

    (1992)
  • J.P. Changeux et al.

    Neuronal models of cognitive functions

    Cognition

    (1989)
  • M.W. Chu

    Balancing the robustness and efficiency of odor representations during learning

    Neuron

    (2016)
  • M. Lövdén

    Structural brain plasticity in adult learning and development

    Neurosci. Biobehav. Rev.

    (2013)
  • D. Meyer

    Balance and stability of synaptic structures during synaptic plasticity

    Neuron

    (2014)
  • S. Tonegawa

    Memory engram storage and retrieval

    Curr. Opin. Neurobiol.

    (2015)
  • M. Bellander

    Behavioral correlates of changes in hippocampal gray matter structure during acquisition of foreign vocabulary

    Neuroimage

    (2016)
  • C.L. Tardif

    Advanced MRI techniques to improve our understanding of experience-induced neuroplasticity

    Neuroimage

    (2016)
  • M. Marjańska

    Region-specific aging of the human brain as evidenced by neurochemical profiles measured noninvasively in the posterior cingulate cortex and the occipital lobe using 1H magnetic resonance spectroscopy at 7 T

    Neuroscience

    (2017)
  • H. Johansen-Berg

    Human structural plasticity at record speed

    Neuron

    (2012)
  • J.P. Lerch

    Maze training in mice induces MRI-detectable brain shape changes specific to the type of learning

    Neuroimage

    (2011)
  • Y. Sagi

    Learning in the fast lane: new insights into neuroplasticity

    Neuron

    (2012)
  • J. Ashburner et al.

    Voxel-based morphometry: the methods

    Neuroimage

    (2000)
  • C. Hutton

    A comparison between voxel-based cortical thickness and voxel-based morphometry in normal aging

    Neuroimage

    (2009)
  • W.T. Greenough

    Effects of rearing complexity on dendritic branching in frontolateral and temporal cortex of the rat

    Exp. Neurol.

    (1973)
  • M. Reuter

    Head motion during MRI acquisition reduces gray matter volume and thickness estimates

    Neuroimage

    (2015)
  • M.F. Glasser

    Trends and properties of human cerebral cortex: correlations with cortical myelin content

    Neuroimage

    (2014)
  • R.J. Dolan et al.

    Goals and habits in the brain

    Neuron

    (2013)
  • E.A. Maguire

    Navigation-related structural change in the hippocampi of taxi drivers

    Proc. Natl. Acad. Sci. U. S. A.

    (2000)
  • B. Draganski

    Changes in grey matter induced by training

    Nature

    (2004)
  • B. Draganski

    Temporal and spatial dynamics of brain structure changes during extensive learning

    J. Neurosci.

    (2006)
  • M. Lövdén

    Spatial navigation training protects the hippocampus against age-related changes during early and late adulthood

    Neurobiol. Aging

    (2012)
  • R. Ilg

    Gray matter increase induced by practice correlates with task-specific activation: a combined functional and morphometric magnetic resonance imaging study

    J. Neurosci.

    (2008)
  • M. Taubert

    Dynamic properties of human brain structure: learning-related changes in cortical areas and associated fiber connections

    J. Neurosci.

    (2010)
  • H. Takeuchi

    Working memory training using mental calculation impacts regional gray matter of the frontal and parietal regions

    PLoS One

    (2011)
  • R.J. Zatorre

    Plasticity in gray and white: neuroimaging changes in brain structure during learning

    Nat. Neurosci.

    (2012)
  • E. Wenger

    Repeated structural imaging reveals nonlinear progression of experience-dependent volume changes in human motor cortex

    Cereb. Cortex

    (2017)
  • Cited by (121)

    View all citing articles on Scopus
    View full text