A Reward-Based Behavioral Platform to Measure Neural Activity during Head-Fixed Behavior.

Andrew H Micallef,Naoya Takahashi,Matthew E Larkum,Lucy M Palmer

doi:10.3389/fncel.2017.00156

Abstract

Understanding the neural computations that contribute to behavior requires recording from neurons while an animal is behaving. This is not an easy task as most subcellular recording techniques require absolute head stability. The Go/No-Go sensory task is a powerful decision-driven task that enables an animal to report a binary decision during head-fixation. Here we discuss how to set up an Ardunio and Python based platform system to control a Go/No-Go sensory behavior paradigm. Using an Arduino micro-controller and Python-based custom written program, a reward can be delivered to the animal depending on the decision reported. We discuss the various components required to build the behavioral apparatus that can control and report such a sensory stimulus paradigm. This system enables the end user to control the behavioral testing in real-time and therefore it provides a strong custom-made platform for probing the neural basis of behavior.

Highlights

Neurons are the building blocks of behavior
The animal is affixed to a stationary apparatus with an implanted head-plate, and licking a sensor is often adopted as a behavioral readout of operant conditioning
We discuss training paradigms associated with the behavior platform and we report on how this platform can be used to measure neural activity during reward-based behavior

Summary

Introduction

Neurons are the building blocks of behavior. to understand the neural basis of behavior, we must record from individual neurons while an animal is active. In response to a rewardable stimulus/situation, an animal may be trained to nose-poke at a given location (Huber et al, 2008; Bussey et al, 2012; Nithianantharajah et al, 2013), press a lever (Lederle et al, 2011), or navigate through a particular sensory environment (van Praag et al, 2000; Znamenskiy and Zador, 2013) These behavioral tests require physical movement of the animal and Measuring Neuronal Activity during Behavior probing the associated neural activity typically involves gross recording techniques such as multi-unit electrophysiology (Epsztein et al, 2011; Stensola et al, 2012; Whitlock et al, 2012). The animal is affixed to a stationary apparatus with an implanted head-plate, and licking a sensor is often adopted as a behavioral readout of operant conditioning

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