Changes in brain structure during learning: fact or artifact? Reply to Thomas and Baker
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In their review in this issue, Thomas and Baker question the validity of longitudinal human neuroimaging studies that have claimed to demonstrate structural plasticity. This commentary identifies problems with some of the arguments raised in their review and suggests that there is strong evidence, from both animal and human studies, that experience can alter brain structure.
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Candidate non-neuronal mechanisms for gray matter changes include angiogenesis and astrocytic changes.
“Most promising neuronal mechanisms underlying gray matter changes include axon sprouting, dendritic branching and synaptogenesis, or neurogenesis (in the hippocampus), while angiogenesis or astrocytic changes are discussed as non-neuronal factors (Fields, 2013;Johansen-Berg, 2012).”
From Serotonin and neuroplasticity – Links between molecular, functional and structural pathophysiology in depression (2017) · cites this paper as Fields, 2013
In the opening section (page unavailable), Fields lists changes in glial numbers, cell morphology, and vascular cells among structural changes found after learning. These support the broader idea of non-neuronal changes, but the paper does not specifically identify angiogenesis or astrocytic changes as mechanisms of gray-matter change. (LLM, conf=0.83)
Experimental — accuracy not yet measuredCandidate neuronal mechanisms for gray matter changes include axon sprouting, dendritic branching, synaptogenesis, and hippocampal neurogenesis.
“Most promising neuronal mechanisms underlying gray matter changes include axon sprouting, dendritic branching and synaptogenesis, or neurogenesis (in the hippocampus), while angiogenesis or astrocytic changes are discussed as non-neuronal factors (Fields, 2013;Johansen-Berg, 2012).”
From Serotonin and neuroplasticity – Links between molecular, functional and structural pathophysiology in depression (2017) · cites this paper as Fields, 2013
The opening section (page not specified) lists axon sprouting, dendritic complexity, synaptic density, and changes in neuronal numbers among cellular changes found after learning. These broadly support several proposed neuronal mechanisms, but the paper does not specifically identify hippocampal neurogenesis or rank the listed mechanisms as the most promising. (LLM, conf=0.85)
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References 17 · Cited by 19
- Authors
- Fields, R. D.
- Affiliations
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (US)
- Corresponding author
- Fields, R. Douglas
- ORCID
- Fields, R. Douglas
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2013-06
- Volume
- 73
- Pages
- 260-264
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC4476622
- OpenAlex
- W2055424641
- Cited by
- 19
- References
- 17
- Citations by year
- 2022: 1 · 2020: 2 · 2019: 1 · 2018: 2 · 2017: 2 · 2015: 2 · 2014: 5 · 2013: 3 · 2012: 1
- FWCI
- 1.19
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- NICHD
- Topics
- Life Sciences › Neuroscience › Developmental Neuroscience › Neurogenesis and neuroplasticity mechanisms
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Keywords
- structural plasticity, brain structure, learning, longitudinal neuroimaging, brain structural changes
- MeSH terms
- Brain, Humans, Learning, Neuronal Plasticity
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