Conjunctive input processing drives feature selectivity in hippocampal CA1 neurons

摘要

Feature-selective firing allows networks to produce representations of the external and internal environments. Despite its importance, the mechanisms generating neuronal feature selectivity are incompletely understood. In many cortical microcircuits the integration of two functionally distinct inputs occurs nonlinearly through generation of active dendritic signals that drive burst firing and robust plasticity. To examine the role of this processing in feature selectivity, we recorded CA1 pyramidal neuron membrane potential and local field potential in mice running on a linear treadmill. We found that dendritic plateau potentials were produced by an interaction between properly timed input from entorhinal cortex and hippocampal CA3. These conjunctive signals positively modulated the firing of previously established place fields and rapidly induced new place field formation to produce feature selectivity in CA1 that is a function of both entorhinal cortex and CA3 input. Such selectivity could allow mixed network level representations that support context-dependent spatial maps. The neuronal microcircuit is a fundamental processing unit of nervous systems and as such is intricately involved in producing the network computations that drive behavior. Many cortical micro-circuits show a stereotyped organization that may allow them to implement a common set of core operations. One such core operation is derived from the fact that most cortical microcircuits receive at least two functionally distinct afferent inputs from different brain areas. In pyramidal neuron-based microcircuits, these different inputs are spatially segregated, with long-range inputs mainly innervating the most distal apical tuft dendrite regions and more local inputs usually forming synapses onto the proximal perisomatic dendrites. The electrical isolation present in most pyramidal neurons means that each functional class of inputs is initially processed in relative independence of the other. However, active dendritic mechanisms, such as backpropagating action potentials (APs) and dendritic Ca2+ plateau potentials, allow the different afferent input streams to interact nonlinearly when they arrive with appropriate coincident timing. Additionally, the initiation of dendritic plateau potentials is known to robustly induce rapid and long-lasting changes in synaptic strength and dendritic excitability. This form of input interaction or integration could support a nonlinear combination of the input streams to produce neurons with a feature selectivity that is a function of both input paths. Such a population will, in turn, generate mixed or multimodal network representations with advantageous computational properties.