Toward a Neuroscience Model of Tort Law: How Functional Neuroimaging Will Transform Tort Doctrine

Abstract:     
The “neuroscience revolution” has now gained the attention of legal thinkers and is poised to be the catalyst for significant changes in the law. Over the past several decades, research in functional neuroimaging has sought to explain a vast array of human thought processes and behaviors, and the law has taken notice. Although functional neuroimaging is not yet close to being a staple in the courtroom, the information acquired from these studies has been featured in a handful of cases, including a few before the United States Supreme Court. Our assertion involves the incorporation of functional neuroscience evidence in tort law related to the variety of mental states, including intent, knowledge, recklessness, and negligence. As the courts become saturated with neurimaging evidence, it is imperative to be prepared with a framework for addressing the many legal questions that the new neuroscience will pose. Our proposed neuroscience model of tort law is both simple and complex. Its simplicity lies in a workable framework for allowing the law to move forward while incorporating functional neuroimaging evidence in tort law. Its complexity is in the challenges posed by the interpretation of the neuroscience data and by extrapolation from the evidence to the legal issues. Our model is intended to commence the discourse about ways in which tort law may be improved through an understanding of, and appropriate use of, information acquired through the newest technologies of functional neuroimaging. We intend this model to provide guidance to judges and attorneys when confronted with functional neuroimaging evidence in tort cases, and we anticipate that serious consideration of the model will propel courts toward incorporating these relevant social and scientific advances into the evolving principles of tort law.

Number of Pages in PDF File: 73

Keywords: tort law, torts, neuroscience, neuroimaging, evidence

JEL Classification: K13

Accepted Paper Series