Functional consequences of age-related morphologic changes to pyramidal neurons of the rhesus monkey prefrontal cortex
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Layer 3 (L3) pyramidal neurons in the lateral prefrontal cortex (LPFC) of rhesus monkeys exhibit dendritic regression, spine loss and increased action potential (AP) firing rates during normal aging. The relationship between these structural and functional alterations, if any, is unknown. To address this issue, morphological and electrophysiological properties of L3 LPFC pyramidal neurons from young and aged rhesus monkeys were characterized using in vitro whole-cell patch-clamp recordings and high-resolution digital reconstruction of neurons. Consistent with our previous studies, aged neurons exhibited significantly reduced dendritic arbor length and spine density, as well as increased input resistance and firing rates. Computational models using the digital reconstructions with Hodgkin-Huxley and AMPA channels allowed us to assess relationships between demonstrated age-related changes and to predict physiological changes that have not yet been tested empirically. For example, the models predict that in both backpropagating APs and excitatory postsynaptic currents (EPSCs), attenuation is lower in aged versus young neurons. Importantly, when identical densities of passive parameters and voltage- and calcium-gated conductances were used in young and aged model neurons, neither input resistance nor firing rates differed between the two age groups. Tuning passive parameters for each model predicted significantly higher membrane resistance (R m ) in aged versus young neurons. This R m increase alone did not account for increased firing rates in aged models, but coupling these R m values with subtle differences in morphology and membrane capacitance did. The predicted differences in passive parameters (or parameters with similar effects) are mathematically plausible, but must be tested empirically.
KeywordsNeuronal excitability Dendrites Spines Morphology Compartment model Aging Rhesus monkey Passive parameters
Special thanks to Alfredo Rodriguez and Douglas Ehlenberger for development and support of software tools used in 3D reconstructions and morphometric analyses. This work was supported by the National Institutes of Health (grant numbers P01 AG00001, R01 AG025062, R01 AG035071, R01 MH071818, and R01 DC05669).
Conflict of interest
The authors declare that they have no conflict of interest.
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