Neurobiologically-informed risk assessment: An empirical examination

需要预测谁将再次犯罪、复发或康复是临床和法律从业者的重要责任，也是向具有不同风险需求的受审个人提供有效医疗保健和社会服务的先决条件。人们普遍认为，大脑在塑造反社会行为方面起着至关重要的作用，但人们对这些过程的确切性质知之甚少。以前的学术研究提出了一种可能性，即通过将大脑功能的测量与传统的行为和社会测量一起包括在内，可以改进评估被判定个人的风险的方法。该项目研究纳入非侵入性大脑测量是否可以增强正确区分最有可能和最不可能经历反社会后果(如再次逮捕)的囚犯的能力。该项目还支持学生在认知神经科学方面的培训和专业发展。该项目的成果预计将支持开发临床工具、程序和治疗方法，以评估和补救法医人群的风险，从而减少社会的相关成本。这个项目的目标是通过对持续性反社会行为的神经认知模型进行第一次大规模的、样本外的纵向测试来实现的。该模型是在600名成年刑事罪犯中开发的，他们接受了任务驱动的功能磁共振成像，并在出狱12个月后接受了再犯罪风险评估(训练样本)。然后，这个模型被用来对100名接受类似扫描、释放和跟踪的刑事罪犯的单独样本(测试样本)进行分类。该项目采用了理论驱动(脉冲控制神经认知模型的零假设检验)和数据驱动(例如，全脑机器学习分类)分析方法。这个项目将通过描述神经生物学和行为风险因素在评估风险时的组合和相对效用，促进关于神经生物学和行为风险因素如何相互作用产生反社会行为的基础和临床知识。这些知识反过来可以用来指导对个别被告独特的风险需求更加敏感的治疗方法的开发。这一裁决反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The need to anticipate who will reoffend, relapse, or recover is an important responsibility of clinical and legal practitioners and a prerequisite for the provision of effective healthcare and social services to adjudicated individuals with different risk-needs. It is widely accepted that the brain plays an essential role in shaping antisocial behaviors, but the precise nature of these processes is poorly understood. Previous scholarship has raised the possibility that methods of assessing risk in adjudicated individuals could be improved by including measures of brain function along with traditional behavioral and social measures. This project examines whether the inclusion of noninvasive brain measures can enhance the ability to correctly distinguish between those inmates most and least likely to experience antisocial outcomes, such as rearrest. The project also supports the training and professional development of students in cognitive neuroscience. The results of this project are expected to support the development of clinical tools, procedures and treatments for assessing and remediating risk in forensic populations, thereby reducing the associated costs to society. The objectives of this project are achieved by conducting the first large, out-of-sample longitudinal test of a neurocognitive model of persistent antisocial behavior. The model is developed in a sample of 600 adult criminal offenders who have undergone task-driven functional magnetic resonance imaging and been assessed for reoffense risk 12 months following release from prison (the training sample). This model is then used to classify a separate sample of 100 criminal offenders who are similarly scanned, released, and followed (the testing sample). The project employs both theory-driven (null hypothesis testing of a neurocognitive model of impulse control) and data-driven (e.g., whole-brain machine learning classification) analytical approaches. This project will advance basic and clinical knowledge of how neurobiological and behavioral risk factors interact to produce antisocial behavior by characterizing their combined and relative utility in assessing risk. This knowledge can, in turn, be used to inform the development of treatment approaches that are more sensitive to individual defendants' unique risk needs.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.