Circuitry underlying response summation in mouse and primate: Theory and experiment

Project Summary Despite the enormous complexity of the brain, it is becoming increasingly apparent that structures like the cerebral cortex are modular, relying on a set of canonical computations that occur across brain regions and modalities to mediate perception, cognition and behavior. One important example of a canonical computation is the summation of various driving, contextual, and modulatory neuronal inputs to yield spiking output. The question of how cortical networks integrate these inputs and transform them into spiking outputs of individual neurons is of central importance to neuroscience. A significant challenge to understanding these computations is that each neuron is embedded within a larger circuit of neurons, each modulating one another?s activity. So, understanding how a particular neuron responds to input necessarily involves understanding the larger circuit. Recent optogenetic studies have found different patterns of input summation in mouse vs. monkey V1. Recently developed theoretical models have produced specific predictions about the differences in network circuitry that can lead to differences in summation, and predict how summation non-­linearities depend on inputs to the network. The proposed research will test these predictions and seek to understand these circuit computations using a combination of theoretical work and optogenetic modulation of circuits in mouse and monkey. Aim 1: Varying E and I optogenetic stimulation and visual contrast independently to measure spike response summation to multiple inputs. In this Aim, theoretical models of input summation across varying cortical circuit regimes will be developed, and recently developed optogenetic tools will be used in awake mouse and monkey V1 to test predictions generated by these models and identify the corresponding regimes. The optogenetic tools include a new viral strategy that directs expression of different opsins to inhibitory vs. excitatory neocortical neurons in the macaque. Simultaneous and independent activation of E and I and the visual stimulus, all within this theoretical framework, will enable us to test whether observed differences in summation properties reflect fundamental species differences or reflect a common computation operating in different parameter regimes. Aim 2: Determine the circuit elements controlling dynamics of cortical network responses using dynamic optogenetic stimulation. In this Aim, experiments using dynamic optogenetic and visual stimulation patterns and theoretical analysis of the models with dynamic inputs will be used to elucidate the temporal dynamics of summation. Aim 3: Determine if different inhibitory subclasses control different aspects of input integration. Different inhibitory subclasses will be stimulated optogenetically to decipher their respective roles in input summation. Taken together, these Aims will help define the roles played by excitatory and inhibitory neurons in mediating summation of neuronal inputs to yield spiking output. This information will be critical for understanding brain disorders associated with failures in perception and attention, as is seen with autism, schizophrenia, and Alzheimer?s disease.