Machine Learning Approaches for Neuroscientific Behavioral Analysis: A Neuromarketing perspective

Neuromarketing has evolved from the fusion of neuroscience and marketing techniques. It intends to measure the interest, attitude, and behavior of consumers towards either any product, service, design, or advertisement. The probable study of various neuroscience techniques with machine learning classification and prediction algorithms is have been studied. Early literature pertaining to neuromarketing is primarily focused on individual techniques, application areas, ethics, datasets, algorithms. This manuscript intends to extend a previous literature by studying essential machine learning techniques, prominent datasets, algorithms, and available equipment for designing neuroscientific experiments. The manuscript concluded with the probable pros and cons of using different machine learning techniques associated with contemporary use of neuroscientific methods. Towards machine learning techniques has many applications in the field of Brain computer interface (BCI), neuromarketing, neurophysiology and clinical neuroscience. In neuromarketing, these techniques help in improving product sales, return on investment, product design etc.