Skip to main content
  • Poster presentation
  • Open access
  • Published:

Age-related neuromorphological distortion affects stability and robustness in a simulated test of spatial working memory

Normal aging in humans and nonhuman primates is associated with cognitive decline, particularly in tasks involving working memory function that relies on the prefrontal cortex [1]. Because normal aging is not correlated with widespread neuron death or gross morphological degeneration, the biological substrate of these deficits remains unclear [2]. We have constructed a simulated network of model neurons with sufficient detail to model age-related perturbations to morphology and network connectivity, in order to investigate the extent to which these morphological changes in single neurons could explain the functional degradation.

Spatial working memory can be modeled with a "bump"-style network of recurrently connected model neurons, characterized by a continuum of dynamical attractor states that provide an analogue of working memory of spatial orientation [3]. A bump-attractor network (Figure 1) was constructed using branching compartmental models of layer 2/3 neocortical pyramidal neurons [4]. Spine number and density are reduced with age in this neuron type [5], a morphological perturbation that was modeled as a reduction in both recurrent network connectivity and equivalent dendritic surface area. Network function was quantified in terms of the dynamical stability of network attractor states during the delay period of a simulated memory task, as well as the robustness of task performance against perturbation of network parameters. Stability and robustness were compared between "young" and "aged" model neuron populations with the multi-dimensional stability manifold method, which has been used in a previous study to examine the dependence of network simulations on modeling methodology [6].

Figure 1
figure 1

"Bump" attractor network model receiving input encoding the direction '315°' (green neuron), with fully interconnected populations of layer 2/3 pyramidal neurons and GABAergic interneurons. Neurons are arranged in direction-selective columns. Directionally-tuned input arrives along afferent collaterals (black arrows). Excitatory connections project preferentially to cells in similarly tuned columns (weighting in inset, upper right).

By defining a stability manifold, we demonstrate how stability and robustness can be quantified as a function of biologically relevant perturbations to single cell morphology and network parameters. This provides a novel technique for evaluating the functional significance of local morphological changes, caused by age, disease or injury, upon cognition at the organism scale.


  1. Gallagher M, Rapp PR: The use of animal models to study the effects of aging on cognition. Annu Rev Psychol. 1997, 48: 339-70. 10.1146/annurev.psych.48.1.339.

    Article  PubMed  CAS  Google Scholar 

  2. O'Donnell KA, Rapp PR, Hof PR: Preservation of prefrontal cortical volume in behaviorally characterized aged macaque monkeys. Exp Neurol. 1999, 160: 300-310. 10.1006/exnr.1999.7192.

    Article  PubMed  Google Scholar 

  3. Tegnér J, Compte A, Wang X-J: The dynamical stability of reverberatory neural circuits. Biol Cybern. 2002, 87: 471-481. 10.1007/s00422-002-0363-9.

    Article  PubMed  Google Scholar 

  4. Traub RD, Contreras D, Cunningham MO, Murray H, LeBeau FEN, Roopun A, Bibbig A, Wilent WB, Higley MJ, Whittington MA: Single-column thalamocortical network model exhibiting gamma oscillations, sleep spindles, and epileptogenic bursts. J Neurophysiol. 2005, 93: 2194-2232. 10.1152/jn.00983.2004.

    Article  PubMed  Google Scholar 

  5. Kabaso D, Nilson J, Luebke JI, Hof PR, Wearne SL: Electrotonic analysis of morphologic contributions to increased excitability with aging in neurons of the prefrontal cortex of monkeys. Program number 237.10. 2006 Abstract Viewer and Itinerary Planner. 2006, Washington, DC: Society for Neuroscience

    Google Scholar 

  6. Coskren PJ, Hof PR, Wearne SL: Stability and robustness in an attractor network are influenced by degree of morphology reduction. Poster S.97, CNS*. 2006

    Google Scholar 

Download references


Supported by NIH grants MH071818, DC05669, AG02219, AG05138.

Author information

Authors and Affiliations


Corresponding author

Correspondence to Patrick J Coskren.

Rights and permissions

Open Access This article is published under license to BioMed Central Ltd. This is an Open Access article is distributed under the terms of the Creative Commons Attribution 2.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and permissions

About this article

Cite this article

Coskren, P.J., Hof, P.R. & Wearne, S.L. Age-related neuromorphological distortion affects stability and robustness in a simulated test of spatial working memory. BMC Neurosci 8 (Suppl 2), P169 (2007).

Download citation

  • Published:

  • DOI: