The long-range goal of this research project is to determine the fundamental mechanisms of information processing in central neurons. Most neurons of the mammalian CNS receive information through synaptic input that is located predominately within dendritic arborizations. It is here, in the dendrites, that thousands of excitatory and inhibitory synaptic inputs are blended together to form a coherent output response (this is known as dendritic integration). The morphology and active membrane properties of neuronal dendrites, therefore, play a very important role in the processing of incoming synaptic activity. Because synaptic input is widely spread across dendritic arborizations, the type of processing performed by the dendrites can vary dramatically as a function of the exact location of the synapse. This potentially large location-dependent synaptic variability has been shown to have detrimental effects on the processing capabilities of neurons. We sought to investigate the role that dendritic voltage-gated ion channels might have in reducing location-dependent synaptic variability. Several lines of preliminary evidence indicate that there is, contrary to theoretical expectations, minimal location-dependence to the individual components of dendritic integration (unitary EPSP amplitude, spatial summation and temporal summation). Furthermore we have preliminarily observed that the properties of the dendrites are responsible for this lack of location- dependence. Finally we have begun to show that by reducing the intrinsic location-dependence of dendritic processing the active properties of the dendrites improve the functional capabilities of CA1 pyramidal neurons. Thus, the central hypotheses to be tested is: dendritic ion channels reduce the location-dependence of synaptic input in hippocampal CA1 pyramidal neurons, improving their computational properties. The proposed studies will provide a more thorough understanding of the mechanisms involved in the integration of synaptic activity within dendrites and will therefore fundamentally advance our understanding of neuronal function.
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