THE CLINICAL NEUROPSYCHOLOGIST https://doi.org/10.1080/13854046.2018.1523465 SPECIAL ISSUE ARTICLE National Institutes of Health initiatives for advancing scientific developments in clinical neuropsychology Thomas D. Parsonsa,b,c and Tyler Duffieldd aNetDragon Digital Research Centre, Denton, Texas; bComputational Neuropsychology and Simulation (CNS) Laboratory, Denton, Texas; cCollege of Information, Denton, Texas; dDepartment of Family/Sports Medicine, Oregon Health and Science University, Portland, Oregon, USA ABSTRACT ARTICLE HISTORY Objective: The current review briefly addresses the history of Received 14 March 2018 neuropsychology as a context for discussion of developmental Accepted 8 September 2018 milestones that have advanced the profession, as well as areas where the progression has lagged. More recently in the digital/ KEYWORDS information age, utilization and incorporation of emerging tech- Neuropsychology 3.0; technologies: National nologies has been minimal, which has stagnated ongoing evolu- Institutes of Health; office tion of the practice of neuropsychology despite technology of behavioral and social changing many aspects of daily living. These authors advocate for sciences research; embracing National Institutes of Health (NIH) initiatives, or inter- neuroinformatics changeably referred to as transformative opportunities, for the behavioral and social sciences. These initiatives address the need for neuropsychologists to transition from fragmented and data- poor approaches to integrated and data-rich scientific approaches that ultimately improve translational applications. Specific to neuropsychology is the need for the adoption of novel means of brain–behavior characterizations. Method: Narrative review Conclusions: Clinical neuropsychology has reached a develop- mental plateau where it is ready to embrace the measurement science and technological advances which have been readily adopted by the human neurosciences. While there are ways in which neuropsychology is making inroads into these areas, a great deal of growth is needed to maintain relevance as a scien- tific discipline (see Figures 1, 2, and 3) consistent with NIH initia- tives to advance scientific developments. Moreover, implications of such progress require discussion and modification of training, ethical, and legal mandates of the practice of neuropsychology. Clinical neuropsychology has a rich tradition of developing validated assessment tools using basic low dimensional technologies (i.e. pencil-and-paper protocols that are not ecologically valid simulations of everyday activities). These tools have undergone a number of apparent advances in quantitative methodologies (e.g. expanded normative CONTACT Thomas D. Parsons [email protected] NetDragon Digital Research Centre, Director, Computational Neuropsychology and Simulation (CNS) Laboratory, Professor of Psychology and of Learning Technologies, University of North Texas, Fellow, National Academy of Neuropsychology, 1155 Union Circle #311280, Denton, TX 76203, USA ß 2018 Informa UK Limited, trading as Taylor & Francis Group 2 T. D. PARSONS AND T. DUFFIELD standards) throughout the profession’s history (e.g. Casaletto & Heaton, 2017). However, neuropsychologists have been slow to embrace emerging technological advances in the digital/information age (Rabin et al., 2014; Rabin, Paolillo, & Barr, 2016). As a result, current neuropsychological assessment procedures represent a tech- nology that has barely changed since the first scales were developed in the early 1900s (Miller & Barr, 2017; Parsons, 2016). A result of this stagnation would be neuro- psychology falling behind current National Institutes of Health (NIH) initiatives to advance scientific developments, including: (1) Integrating neuroscience into behav- ioral and social sciences; (2) Transformative advances in measurement science; (3) Digital intervention platforms; and (4) Large scale population cohorts and data integra- tion (Collins & Riley, 2016). Relatedly, the NIH Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative endeavors to uncover the mysteries of brain disorders (e.g. Alzheimer’s, Parkinson’s, depression, and traumatic brain injury) and accelerate the development of new technologies for producing dynamic brain imaging and modeling (Insel, Lands, & Collins, 2013). The NIH has developed a 12-year research strategy to achieve the goals of the initiative. For neuropsychologists interested in keeping pace with NIH initiatives (e.g. the NIH BRAIN initiative), there is a unique opportunity to take part in the development of technologies for exploration into the ways in which the brain records, processes, uses, stores, and retrieves vast quantities of information. Furthermore, neuropsychologists can help shed light on neuroscience findings through clinical expertise to aid our understanding of the complex links between brain function and behavior. After a brief discussion of the historical progression of neuropsychological assess- ment technologies, there will be a discussion of current NIH initiatives for the behav- ioral and social sciences. This will include evaluations of current neuropsychological assessment technologies and approaches for maintaining relevance as a specialty. 1. Brief historical overview of neuropsychology and technology Numerous advances from qualitative to more quantitative methods have occurred since neuropsychology’s inception, such as expanded normative standards (Casaletto & Heaton, 2017), evidence-based indicators of neuropsychological change (e.g. Duff, 2012), performance validity testing (e.g. Greher & Wodushek, 2017), and cross-cultural considerations regarding limits of normative comparisons, daily life relevance of test content, familiarity with the testing process, etc. (e.g. Olson & Jacobson, 2015). While each of these advances has been meaningful for the investigation of cognitive func- tions, the importance of modernizing current approaches to neuropsychological assessment in light of technological advances has received increasing interest of late (e.g. Beaumont, 2008; Benton & Sivan, 2007; Bilder, 2011; Casaletto & Heaton, 2017; Jagaroo, 2009; Jagaroo & Santangelo, 2017; Miller & Barr, 2017; Parsons, 2016; Ponsford, 2017). Miller and Barr (2017) provide a useful brief history of neuropsychol- ogy’s limited adoption of technology and the maintenance of low dimensional paper- and-pencil measures due to the profession’s relationship with test publish- ing companies. THE CLINICAL NEUROPSYCHOLOGIST 3 Bilder (2011) argues that three periods in time represent clinical neuropsychology’s scientific development. From 1950–1979, Neuropsychology 1.0 was a period in which lesion localization and interpretation were emphasized without thorough normative data. From 1980 to the present, one finds Neuropsychology 2.0, wherein technological advances in neuroimaging shifted the focus from lesion localization to characterization of cognitive strengths and weaknesses using normative batteries. Bilder sees Neuropsychology 3.0 as a future period of neuropsychological advancement that will incorporate findings from neuroinformatics and information technologies. In a similar fashion, Parsons (2016) appraised the technological and theoretical development of neuropsychological assessment in terms of three waves of techno- logical adoption. Parsons argues that Neuropsychology 1.0 is best understood as a period in which neuropsychological assessments emphasized the development of low dimensional and construct-driven (i.e. simple stimulus presentations of stimuli to test abstract concepts like working memory) paper-and-pencil measures. Neuropsychology 2.0 represents a technological move to automate the administration, scoring, and in some instances the interpretation of low dimensional stimulus presentations using computerized approaches (NIH Toolbox; Gershon et al., 2010, 2013; Weintraub et al., 2013), as well as teleneuropsychology (e.g. video teleconferencing; Cullum, Hynan, Grosch, Parikh, & Weiner, 2014). The NIH Toolbox is an example of a computerized assessment battery initiated by the NIH Blueprint for Neuroscience Research that is developing a normative database (Gershon et al., 2010, 2013; Weintraub et al., 2013). The goal was to develop a set of computerized neuropsychological measures to enhance collection of data in large cohort studies and to advance biomedical research (Gershon et al., 2010, 2013; Weintraub et al., 2013). With synchronous developments in neuroimaging during this era, neuropsychologists were increasingly called upon to make predictions about the patient’s ability to perform activities of daily living. As such, Neuropsychological Assessment 3.0 reflects the contemporary development of high dimensional (ecologically valid simulation of everyday activities) assessment and rehabilitation technologies (e.g. computational modeling and simulation; virtual reality; deep learning; neuroinformatics). These historical formulations are not without controversy. One area of historical concern has been that computerized assessments may result in increased error (e.g. program shutting down mid-way through subtest; e.g. Cernich, Brennana, Barker, & Bleiberg, 2007) and/or decreased integrity of the neuropsychological evaluation pro- cess by means of automation. While many of these concerns have been addressed with advances in computational power and security, there are a number of steps that need to be taken on the part of developers and users of computerized assessments