Marrying the past and present neuropsychology: Is the future of the process-based approach technology-based?
Frontiers in Psychology (2020). 11.
Standardized neuropsychological tests have historically been focused on ecological validity. Many non-cognitive variables, such as physical, behavioral and emotional factors, and levels of premorbid functioning could be responsible for a deviation from real-world behavior. Throughout these tests, three main factors emerge that have the potential to hamper the ecological validity of neuropsychological test performances: a relatively sterile testing environment in which cognitive tests are conducted (a distraction-free environment that isolates sensorial modalities and controls environmental conditions like noise or temperature), a limited sample of behavior (neuropsychological tests performed over a relatively limited period of time, bestowing less information as opposed to complex cognitive processes that require a larger amount of time to complete), and a lack of agreement regarding the specific cognitive constructs (a lack of consensus makes it difficult to align any particular cognitive test scores to an appropriate cognitive skill in a real-world setting). In an effort to overcome these limitations, new methods of assessing cognitive functions have been proposed in recent years. Future research is focused on performance-based tests that will be administered in realistic environments accompanied by the usage of technology and Virtual Reality (VR).
A few of the most common standardized neuropsychological tests include the Clock Drawing Test, the Trail Making Test, the Block Design, and Digital Span. It has been proposed to implement machine-learning algorithms with advanced technology. For example, on the Clock Drawing Test, the patient is asked to draw the face of a clock and the corresponding numbers. Factors such as drawing time, pauses and hesitations in drawing, and time spent holding the pen but not drawing, are recorded with 12 milliseconds accuracy in this research. This machine can automate time-consuming and subjective processes, analyzing difficult data for clinicians to interpret manually and helping detect cognitive impairment at an earlier stage than is currently possible. For the Trail Making Test (TMT), throughout the process, they are monitored for speed for attention, sequencing, mental flexibility, visual search, and motor function. As time went on, an introduction of a computerized version of the TMT reduced the influence of the examiner, automatically corrected errors, equated Trails A and Trails B path lengths, and presented a standardized TMT display throughout the test that is consistent across subjects. For the Block Design, subjects are required to assemble red, white, or red-and-white blocks in three-dimensional space based on a presentation of a two-dimensional stimulus card, which assesses their visual-spatial ability, constructional praxis, motor skill, and problem-solving skill ability. Recently, haptic VR systems or augmented reality systems have been implemented, allowing the use of real blocks while capturing performance more accurately. These technological devices permit the registration of the full sequence of performance while capturing and documenting the different types of errors and performance: stimulus bound, broken configurations, rotations, completion times, think-time, psychomotor slowing, etc. For Digital Span, subjects are required to keep in mind and then recall increasingly lengthy series of digits for a short time period, which assesses auditory span and working memory. Within the past few years, the development of computerized error analysis in the DS, identifying two general types of errors (item errors and order errors) was implemented into Digital Span. Item errors relate to an omission, addition, intrusion, or substitution in the string of numbers, whereas, order errors relate to an incorrect order or permutation error in the string of numbers. This computerized error analysis improves test sensitivity, as it improves the accuracy of the assessment of list length and serial-position effects, error analysis, and detection of idling. With all this being said, the technological aspect of each analysis possibly can enhance the standard version, thus increasing ecological validity and more suitable rehabilitation processes.
With all this evidence, the question that arises is whether we could take advantage of computer-based technologies to improve error analysis? Specifically, can we identify disease-specific error patterns and behaviors more accurately than what can currently be achieved manually by clinicians? In relation to this question, we would argue that VR technology might allow neuropsychology to reach this next level. Today, the amount of technology we possess has the potential to show an immersive interactive virtual environment at a reasonable cost. With the implementation of VR, a new paradigm of human-computer interaction becomes more prevalent, where external observers are able to view progress and images on a computer screen, while the active participant is immersed in a computer-generated virtual 3D world. Nevertheless, we are able to find the possibility to show dynamic and interactive 3D stimuli systematically within a virtual environment, which is impossible by other means. With the ability to create an evaluation environment that can increase ecological validity, immediate feedback through sensorial modalities, capture test performance, and other forms of feedback, a safer environment is generated, which leads to more accurate judgments and results. Performing more accurate judgments and predictions of a patient’s daily life, including such things as school or work performance, could ultimately support the development of more personalized rehabilitation programs. Although VR and technology are not the remedies for all types of behavioral analysis and continue to be perfected, they represent a great opportunity in the future in terms of usability and usefulness in the neuropsychology arena.
Joseph Young
Psychology Intern
Here at NRS|LS, we believe understanding the interface between technology and neuropsychological advancements is critical in order to provide the best patient care.