Neuropsychology has fallen reliant on outdated and labor intensive methods of data collection that are slow, highly inefficient, and expensive, and provide relatively data-poor estimates of human behavior despite rapid technological advance in most other fields of medicine. Here we present a brief historical overview of current testing practices in an effort to frame the current crisis, followed by an overview of different settings in which technology can and should be integrated. Potential benefits of laboratory based assessments, remote assessments, as well as passive and high-frequency data collection tools rooted in technology are discussed, along with several relevant examples and how these technologies might be deployed. Broader issues of data security and privacy are discussed, as well as additional considerations to be addressed within each setting. Some of the historical barriers to adoption of technology are also presented, along with a brief discussion of the remaining uncertainties. While by no means intended as a comprehensive review or prescriptive roadmap, our goal is to show that there are a tremendous number of advantages to technologically driven data collection methods, and that technology should be embraced by the field. Our predictions are that the comprehensive assessments of the future will likely entail a combination of lab-based assessments, remote assessments, and passive data capture, and leading the development of these efforts will cement the role of neuropsychology at the forefront of cognitive and behavioral science.

IntroductionBetter characterization of the relationship between episodic memory and hippocampal volumes is crucial in early detection of neurodegenerative disease. We examined these relationships in a memory clinic population.MethodsParticipants (n = 226) underwent structural magnetic resonance imaging and tests of verbal (Hopkins Verbal Learning Test-Revised, HVLT-R) and non-verbal (Brief Visuospatial Memory Test-Revised, BVMT-R) memory. Correlational analyses were performed, and analyses on clinical subgroups (i.e., amnestic Mild Cognitive Impairment, non-amnestic Mild Cognitive Impairment, probable Alzheimer’s disease, intact memory) were conducted.ResultsPositive associations were identified between bilateral hippocampal volumes and both memory measures, and BVMT-R learning slope was more strongly positively associated with hippocampal volumes than HVLT-R learning slope. Amnestic Mild Cognitive Impairment (aMCI) participants showed specific positive associations between BVMT-R performance and hippocampal volumes bilaterally. Additionally, analyses of the aMCI group showed trend-level evidence of material-specific lateralization, such that retention of verbal information was positively associated with left hippocampal volume, whereas learning curve and retention of non-verbal information was positively associated with right hippocampal volume.ConclusionsFindings support the link between episodic memory and hippocampal volumes in a memory clinic population. Non-verbal memory measures also may have higher diagnostic value, particularly in individuals at elevated risk for Alzheimer’s disease.

Introduction The concordance of the Montreal cognitive assessment (MoCA) with more comprehensive neuropsychological measures remains unclear. This study examined the individual MoCA domains with more comprehensive and commonly used neuropsychological measures to determine the degree of overlap. Methods Data included individuals seen in an outpatient neurology clinic specializing in neurodegenerative disease who were administered the MoCA and also underwent neuropsychological assessment (n = 471). A principal component analysis with varimax rotation was completed using the MoCA domain scores and comprehensive neuropsychological evaluation measures. Results Four factors emerged accounting for 55.6% of the variance: (1) visuospatial/executive functioning; (2) memory; (3) attention; and (4) language. The individual MoCA domain scores demonstrated high factor loadings with standard neuropsychological measures purported to measure similar cognitive constructs. Discussion These findings provide empirical validation for the MoCA domain classifications, lending further support for the use of the MoCA as a cognitive screen that reflects similar constructs as those measured by a comprehensive battery.