Dendrites

Performance motor errors trigger animals’ adaptive learning behaviors to improve the accuracy and efficiency of the movement. The cerebellum is one of the key brain centers for encoding motor performance and motor learning. Climbing fibers relay information related to motor errors to the cerebellar cortex, evoking elevation of intracellular Ca2+ signals at Purkinje cell dendrites and inducing plasticity at coactive parallel fiber synapses, ultimately recalibrating sensorimotor associations to alter behavior. Molecular layer interneurons (MLIs) inhibit Purkinje cells to modulate dendritic excitability and action potential output. How MLIs contribute to the regulation and encoding of climbing fiber-evoked adaptive movements remains poorly understood. In this dissertation, I used genetic tools to manipulate the activity of MLIs while monitoring Purkinje cell dendritic activity during a cerebellum-dependent motor learning task with different contexts to evaluate how MLIs are involved in this process. The results show that by suppressing dendritic Ca2+ signals in Purkinje cells, MLI activity coincident with climbing fiber-mediated excitation prevents the occurrence of learning when adaptation is not necessary. On the other hand, with error signals present, disinhibition onto Purkinje cells, mediated by MLI-MLI microcircuit, unlocked the ability of climbing fibers to induce plasticity and motor learning.

The physical architecture of neural circuits is thought to underlie the computations that give rise to higher order feature sensitivity in the neocortex. Recent technological breakthroughs have allowed the structural and functional investigation of the basic computational units of neural circuits; individual synaptic connections. However, it remains unclear how cortical neurons sample and integrate the thousands of synaptic inputs, supplied by different brain structures, to achieve feature selectivity. Here, I first describe how visual cortical circuits transform the elementary inputs supplied by the periphery into highly diverse, but well-organized, feature representations. By combining and optimizing newly developed techniques to map the functional synaptic connections with defined sources of inputs, I show that the intersection between columnar architecture and dendritic sampling strategies can lead to the selectivity properties of individual neurons: First, in the canonical feedforward circuit, the basal dendrites of a pyramidal neuron utilize unique strategies to sample ON (light increment) and OFF (light decrement) inputs in orientation columns to create the distinctive receptive field structure that is responsible for basic sensitivity to visual spatial location, orientation, spatial frequency, and phase. Second, for long-range horizontal connections, apical dendrites unbiasedly integrate functionally specialized and spatially targeted inputs in different orientation columns, which generates specific axial surround modulation of the receptive field.