Ontogeny of frequency-dependent synaptic plasticity in the dentate gyrus of the immature and adult rodent brain

Information pertaining to the ontogeny of synaptic plasticity in the hippocampus, a brain structure intimately involved in the processes of learning and memory, is important if we are to (1) understand how information processing in the brain is accomplished and (2) develop neural network models of brain plasticity. Two such manifestations of hippocampal synaptic plasticity are long-term depression (LTD) and long-term potentiation (LTP) which are activity-induced alterations in neuronal activity, and have been hypothesized to be critical for learning and memory. Although LTD and LTP have been studied extensively in vitro, to date there have been no systematic examination of the biphasic synaptic plasticity response curve as a function of stimulation frequency in the dentate gyrus in vivo, in general, or in the freely moving animal model, in particular. Thus, the purpose of the present study is to systematically characterize frequency-dependent synaptic plasticity (LTP/LTD) in the perforant path-dentate granule cell synapse in the freely moving animal at two ages of development, i.e. at 15 days of age (preweaning stage) and 90 days of age (adulthood). The measures of synaptic transmission were taken as the amplitude of the population spike (a measure indicative of cellular response) and the slope of the field excitatory postsynaptic potential (EPSP) (a measure indicative of synaptic activation). Our findings indicate that both population spike amplitude and field EPSP slope values showed frequency-dependent alterations in the degree and type of synaptic plasticity, with low frequency stimulation resulting in LTD and higher frequencies yielding LTP. In addition, a development-related shift to the left in the transition from LTD to LTP was observed in the younger animals compared to adult animals at theta frequencies. Taken together, the present findings indicate that both LTP and LTD are modes of synaptic plasticity present in the hippocampus that provide for neuronal gating and information processing in the brain. This information will be important in bettering understanding of how the brain functions and will permit us to design more efficient and realistic mathematical/computational neural networks in the future.