Intrinsic membrane properties determine hippocampal differential firing pattern in vivo in anesthetized rats
نویسندگان
چکیده
The hippocampus plays a key role in learning and memory. Previous studies suggested that the main types of principal neurons, dentate gyrus granule cells (GCs), CA3 pyramidal neurons, and CA1 pyramidal neurons, differ in their activity pattern, with sparse firing in GCs and more frequent firing in CA3 and CA1 pyramidal neurons. It has been assumed but never shown that such different activity may be caused by differential synaptic excitation. To test this hypothesis, we performed high-resolution whole-cell patch-clamp recordings in anesthetized rats in vivo. In contrast to previous in vitro data, both CA3 and CA1 pyramidal neurons fired action potentials spontaneously, with a frequency of ∼3-6 Hz, whereas GCs were silent. Furthermore, both CA3 and CA1 cells primarily fired in bursts. To determine the underlying mechanisms, we quantitatively assessed the frequency of spontaneous excitatory synaptic input, the passive membrane properties, and the active membrane characteristics. Surprisingly, GCs showed comparable synaptic excitation to CA3 and CA1 cells and the highest ratio of excitation versus hyperpolarizing inhibition. Thus, differential synaptic excitation is not responsible for differences in firing. Moreover, the three types of hippocampal neurons markedly differed in their passive properties. While GCs showed the most negative membrane potential, CA3 pyramidal neurons had the highest input resistance and the slowest membrane time constant. The three types of neurons also differed in the active membrane characteristics. GCs showed the highest action potential threshold, but displayed the largest gain of the input-output curves. In conclusion, our results reveal that differential firing of the three main types of hippocampal principal neurons in vivo is not primarily caused by differences in the characteristics of the synaptic input, but by the distinct properties of synaptic integration and input-output transformation.
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