Cited by 460Neuroscience and Neuropharmacology ResearchNeuroinflammation and Neurodegeneration MechanismsNeural dynamics and brain function

Changes in the structural complexity of the aged brain

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Dickstein, Dara L., Kabaso, Doron, Rocher, Anne B., Luebke, Jennifer I., Wearne, Susan L., Hof, Patrick R.·2007·Aging Cell

Abstract

Summary: Structural changes of neurons in the brain during aging are complex and not well understood. Neurons have significant homeostatic control of essential brain functions, including synaptic excitability, gene expression, and metabolic regulation. Any deviations from the norm can have severe consequences as seen in aging and injury. In this review, we present some of the structural adaptations that neurons undergo throughout normal and pathological aging and discuss their effects on electrophysiological properties and cognition. During aging, it is evident that neurons undergo morphological changes such as a reduction in the complexity of dendrite arborization and dendritic length. Spine numbers are also decreased, and because spines are the major sites for excitatory synapses, changes in their numbers could reflect a change in synaptic densities. This idea has been supported by studies that demonstrate a decrease in the overall frequency of spontaneous glutamate receptor‐mediated excitatory responses, as well as a decrease in the levels of α‐amino‐3‐hydroxy‐5‐methylisoxazole‐4‐propionic acid and N‐methyl‐d‐aspartate receptor expression. Other properties such as γ‐aminobutyric acid A receptor‐mediated inhibitory responses and action potential firing rates are both significantly increased with age. These findings suggest that age‐related neuronal dysfunction, which must underlie observed decline in cognitive function, probably involves a host of other subtle changes within the cortex that could include alterations in receptors, loss of dendrites, and spines and myelin dystrophy, as well as the alterations in synaptic transmission. Together these multiple alterations in the brain may constitute the substrate for age‐related loss of cognitive function.

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  • Neurite morphology is a substrate of neural function.

    “Our study tests the hypothesis that the variability of neurite orientations is a biomarker of multiple sclerosis pathology, and is motivated by recent findings demonstrating that neurite morphology is a substrate of neural function23, 24 and is affected by multiple sclerosis.25”
  • The age-related decrease in cortical ODI is in line with histology showing age-related decreases of dendritic complexity and density.

    “which is in line with histology showing age-related decreases of dendritic complexity and density (Dickstein et al., 2007).”

    From NODDI in clinical research (2020) · cites this paper as Dickstein et al., 2007

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  1. Gazzaley AH, Siegel SJ, Kordower JH, Mufson EJ, Morrison JH (1996) Circuit-specific alterations of N-methyl-D-aspartate receptor subunit 1 in the dentate gyrus of aged monkeys. Proc. Natl Acad. Sci. USA 93, 3121-3125.
  2. Henry BI, Hof PR, Rothnie P, Wearne SL (2002) Fractal analysis of aggregates of non-uniformly sized particles: an application to macaque monkey cortical pyramidal neurons. New Jersey: World Scientific Publishing Co, Pty. Ltd.
  3. Jacobsen JS, Wu CC, Redwine JM, Comery TA, Arias R, Bowlby M, Martone R, Morrison JH, Pangalos MN, Reinhart PH, Bloom FE (2006) Early-onset behavioral and synaptic deficits in a mouse model of Alzheimer's disease. Proc. Natl Acad. Sci. USA 103, 5161-5166.
  4. Knowles RB, Wyart C, Buldyrev SV, Cruz L, Urbanc B, Hasselmo ME, Stanley HE, Hyman BT (1999) Plaque-induced neurite abnormalities: implications for disruption of neural networks in Alzheimer's disease. Proc. Natl Acad. Sci. USA 96, 5274-5279.
  5. Lamb BT, Sisodia SS, Lawler AM, Slunt HH, Kitt CA, Kearns WG, Pearson PL, Price DL, Gearhart JD (1993) Introduction and expression of the 400 kilobase amyloid precursor protein gene in transgenic mice. Nat. Genet. 5, 22-30.
  6. Mishizen A, Ikonomovic M, Armstrong DM (2001) Glutamate receptors in aging and Alzheimer's disease. In Functional Neurobiology of Aging (Hof PR, Mobbs CV, eds). San Diego, CA: Academic Press, pp. 283- 314.
  7. Peters A (2002) The effects of normal aging on myelin and nerve fibers: a review. J. Neurocytol. 31, 581-593.
  8. Rall W (1964) Theoretical Significance of Dendritic Trees for Input-Output Relations. Stanford, CA: Stanford University Press.
  9. Samsonovich AV, Ascoli GA (2006) Morphological homeostasis in cor- tical dendrites. Proc. Natl Acad. Sci. USA 103, 1569-1574.
  10. Wu CC, Chawla F, Games D, Rydel RE, Freedman S, Schenk D, Young WG, Morrison JH, Bloom FE (2004) Selective vulnerability of dentate granule cells prior to amyloid deposition in PDAPP mice: digital morphometric analyses. Proc. Natl Acad. Sci. USA 101, 7141- 7146.
  11. Zador AM, Agmon-Snir H, Segev I (1995) The morphoelectrotonic transform: a graphical approach to dendritic function. J. Neurosci. 15, 1669-1682. 14749726, 2007, 3, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/j.1474-9726.2007.00289.x by Mount Vernon Nazarene University, Wiley Online Library on [05/09/2026]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License · DOI

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Authors
Dickstein, D. L., Kabaso, D., Rocher, A. B., Luebke, J. I., Wearne, S. L., & Hof, P. R.
Affiliations
  • Icahn School of Medicine at Mount Sinai (US)
  • Boston University (US)
Corresponding author
Dickstein, Dara L.
Venue
Aging Cell
Publisher
Wiley
Published
2007-03-16
Volume
6
Issue
3
Pages
275-284
ISSN
  • 1474-9718 (ISSN-L)
  • 1474-9726
OpenAlex
W2084792449
Cited by
460
References
9
Citations by year
2026: 15 · 2025: 25 · 2024: 23 · 2023: 27 · 2022: 17 · 2021: 47 · 2020: 23 · 2019: 21 · 2018: 22 · 2017: 16 · 2016: 26 · 2015: 20 · 2014: 14 · 2013: 24 · 2012: 27
FWCI
2.32
Type
journal article
Language
en
Open access
Locations
  • Aging Cell (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • National Institutes of Health
  • National Institute on Aging (AG-02219, AG 05138, P50AG005138, R01AG025062, P01AG000001, AG00001, P01AG002219)
  • National Institute of Mental Health (R01MH071818, MH71818)
  • National Institute on Deafness and Other Communication Disorders (DC05669, R01DC005669)
Topics
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
  • Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
Keywords
brain aging, dendritic branching, dendritic spine loss, synaptic density, glutamate receptors, NMDA receptor, GABAA receptor, action potential firing rate, cognitive decline, synaptic transmission
MeSH terms
Action Potentials, Aged, Aging, Alzheimer Disease, Brain, Dendrites, Electrophysiology, gamma-Aminobutyric Acid, Homeostasis, Humans, Models, Biological, Models, Neurological, Neurons, Receptors, Glutamate, Dendritic Spines

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