The Automated Test of Embodied Cognition (ATEC): History
View Latest Version
Please note this is an old version of this entry, which may differ significantly from the current revision.
Subjects: Neurosciences
Contributor:
Morris David Bell
,
Alexander Joseph Hauser
,
Andrea J. Weinstein

The Automated Test of Embodied Cognition (ATEC) uses video administration of cognitively demanding physical tasks and motion capture technology to assess cognition in action. Embodied cognition is a radical departure from conventional approaches to cognitive assessment and is in keeping with contemporary neuroscience.

  • embodied cognition
  • neuropsychology
  • substance use disorder
  • alcohol use disorder
  • aging
  • cognitive assessment

1. Overview of ATEC

The Automated Test of Embodied Cognition (ATEC) measures cognitive functioning based on cognitively demanding physical tasks assessed using an automated video administration with motion capture technology. Embodied cognition (EC) is a broad framework within cognitive science that emphasizes the importance of somatic sensorimotor experiences with our social and physical environment in developing and shaping our higher cognitive processes [1]. It argues that biological aspects of bodily life are necessary for cognition, affecting our perceptions and our interpretations of experience. Developmental psychology recognizes the key role that sensorimotor information plays in cognitive development and conceptual processes [2], and there is ample evidence that cognitive decline is associated with reduced physical activity and a lack of sensorimotor stimulation [3]. ATEC addresses the need for an assessment instrument that measures the integration of sensorimotor and neurocognitive functioning as a measure of higher cognitive processes in action.
ATEC was the result of a collaboration between computer scientists and psychiatrists, neuropsychologists, neurologists and physical therapists to develop an objective measurement system of embodied cognition for children with a range of neurodevelopmental stages and disorders, funded by a large grant from NSF to Morris Bell, Ph.D, as Co-PI, with a computer science team headed by Fillia Makedon, Ph.D, of the University of Texas, Arlington (National Science Foundation Project #1565310, “Cyber Human Systems Large Collaborative Research: Computational Science for Improving Assessment of Executive Function in Children”). The collaboration produced an automated assessment system with motion capture technology [4] that has been found to be reliable and valid for the assessment of higher cognitive functioning in children. It is a better predictor of day-to-day functioning in children than conventional neuropsychological measures, and differentiates normal children from children at risk of neurodevelopmental disorders [5]. An adult version, with similar assessment tasks and technology but with adult demonstrators and more adult language, has been developed using many tasks from the child version, thus providing a system which can assess people throughout life, from 5 years to 90 years of age.

2. Embodied Cognition (EC): A Novel Construct to Study Sensorimotor/Cognitive Impairment

Sensorimotor and neurocognitive compromise are among the earliest indicators of onset of illness in neurodevelopmental disorders and neurocognitive decline, and they are predictors of functional outcomes [6][7]. Neuropsychological assessments have long been the usual procedures for identifying these impairments, but these tests come from early 20th century understandings of the mind as being separate from the body, and contemporary cognitive testing methods, like the first IQ test (Stanford Binet), remain seated tasks with very little demand for body movement. ATEC measures EC, a cognitive neuroscience framework that addresses critical relationships between cognition and body movement in response to structured activities, in ways that may elude conventional sensorimotor or neurocognitive assessments.
In brief, EC proposes that cognition is shaped by the entire body system. Neuroscience reveals that cognition develops both along with and by way of physical movement [2]. The brain is topographically organized, with multiple parallel basal ganglia–cortical circuits (i.e., motor, limbic, cognitive circuits), so that even higher cortical functions such as working memory and self-regulation (prefrontal cortex) are actually part of complex distributed systems that include cerebellar and subcortical regions previously associated only with movement and balance.
While neuropsychological assessments are anchored in a strong foundation of cognitive science, their procedures are based on disembodied and localizationist–connectionist approaches. Clinical tests rely on classic models of perception–cognition–action that ignore the important sensorimotor system and emotions, while sensorimotor tasks (such as neurological subtle signs (NSS)) do not make higher cognitive demands. Measuring cognition in action is a paradigm shift that is in keeping with contemporary neuroscience. Higher level neurocognitive assessments that require movement are needed, because EC tasks are truer to real-life functions (i.e., they have ecological validity) and capture cognition in action. EC tasks can provide more sensitive assessments because of the greater neurocognitive challenge posed when the whole body is engaged; during EC tasks, higher cognitive functioning is presented in the context of sensorimotor processing, as is the case with dual attention tasks used in neurological assessments [8].

3. Utilizing Novel Digital Approaches to Detect Sensorimotor/Cognitive Impairment

Measuring cognition in action is only now practical because of advances in motion capture technology that make automated administration and scoring possible. The field of digital health technology, which uses a variety of platforms, is growing at a rapid pace and emerging in studies of various neurological conditions [9][10]. Digital technology has become a notable research priority, as evidenced by the 2018 National Academies of Sciences, Engineering, and Medicine’s Forum on Neuroscience and Nervous System Disorders, which addressed the field’s current states and challenges, and the translation of digital technology into meaningful health and societal contributions [10]. With ATEC, researchers have created an automated video administration and a comprehensive scoring system with high fidelity, usability, and efficiency. The motion capture setup uses inexpensive, commercially available equipment, is portable and is user friendly. ATEC incorporates an engaging platform, in which the participant interacts with a recorded “host” who is aided by demonstrators representing gender, age, and racial diversity. Tasks are administered on screen (similarly to an exercise video) ensuring high fidelity and reliability of administration, while allowing users the flexibility to personalize the assessment by selecting tasks appropriate to the reason for referral.
ATEC is a new tool with the potential for detecting sensorimotor/cognitive change during early stages of illness or over the course of recovery by offering novel metrics rather than improvements to older tests [11]. This technology promises to provide sensitive, objective, multidimensional and ecologically valid measurements that reflect subtle changes in behavior or function; thus, it has the potential to produce clinically meaningful outcome measures in clinical practice and research trials. The researchers also have plans for developing a telehealth version for home-based monitoring.

4. ATEC Tasks and Scoring

ATEC consists of tasks from Section 3 of the Movement Disorder Society-Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) and four novel tasks developed specifically for ATEC. The MDS-UPDRS movement tasks include timed-up and go (stand up from a sitting position and walk ten feet, turn around and walk back), tandem walk (walk eight steps heel to toe), the Romberg task (stand with eyes closed and arms outstretched for 10 seconds), balance on one foot (for 10 seconds), foot tap, foot stomp, fist open and close, hand pronation–supination, and finger tap (all tasks repeated for left and right for 10 seconds). There is also a dual attention task that combines timed-up and go with counting backwards from 100 by 7′s. This shows the difference in walking speed with and without cognitive load.
The first of the four novel tasks is marching in place at a slow and fast tempo as a measure of rhythm and coordination without complex cognitive load.
The second novel task, called “red light/yellow light/green light”, assesses sustained attention and response inhibition and requires rhythmic upper body movement in response to commands. The participant is asked to pass a juggling ball from one hand to the other in time with the words “green light”, to move the ball up and down in time with the words “yellow light”, and to not pass the ball when the participant hears “red light”. The task is subsequently repeated at a faster pace. The participant is then presented with the same task, but using a sequence of pictures of green, red, and yellow traffic lights as visual cues, rather than the spoken cues, thus allowing for comparison between sensory modalities.
The third novel task is the “cross your body” task. In beat to a tune, participants are instructed to touch their ears alternately with the opposite hand (left hand to right ear; right hand to left ear) three times, and then the knees three times (lyrics: “cross your body, touch your ears, ears, ears; cross your body, touch your knees, knees, knees”). Then, participants are instructed to touch their knees when the word "ears" is heard, and touch their ears when the word "knees" is heard. The same procedure then replaces ears and knees with hips and shoulders. In the final round, all four commands are given, and the person must remember to touch their knees when "ears" is heard, their ears when "knees" is heard, their hips when "shoulders" is heard, and their shoulders when "hips" is heard. This task requires sustained attention, working memory, response inhibition, cognitive flexibility, and self-regulation. Crossing the midline increases sensitivity for detection of subtle brain compromise and increases cognitive load.
The fourth novel task is an embodied learning and memory task called “map sense”. It requires the participant to remember three, four, and five step movements across a 3 × 3 grid. The steps are sequentially displayed on a map on screen, and then the participant must remember the sequence and move across the grid on the floor in rhythm to a simple tune. There are three trials for each map. The participant is tested again 20 min later without the maps being shown to measure delayed embodied memory recall.
Expert scoring creates raw scores at the item level (e.g., number of finger taps, accurate ball passes), and these raw scores are then categorized so that each component score of each task (e.g., accuracy, rhythm) has equal value. These are added together into domain scores and converted again into a 5-point scale. The domain scores are then added together to give the ATEC total score.

This entry is adapted from the peer-reviewed paper 10.3390/brainsci13060856

References

  1. Varela, F.J.; Thompson, E.; Rosch, E. The Embodied Mind: Cognitive Science and Human Experience; MIT Press: Cambridge, MA, USA, 1991.
  2. Borghi, A.M.; Cimatti, F. Embodied cognition and beyond: Acting and sensing the body. Neuropsychologia 2010, 48, 763–773.
  3. Kraft, E. Cognitive function, physical activity, and aging: Possible biological links and implications for multimodal interventions. Aging Neuropsychol. Cogn. 2012, 19, 248–263.
  4. Dillhoff, A.; Tsiakas, K.; Babu, A.R.; Zakizadehghariehali, M.; Buchanan, B.; Bell, M.; Athitsos, V.; Makedon, F. An automated assessment system for embodied cognition in children: From motion data to executive functioning. In Proceedings of the 6th International Workshop on Sensor-Based Activity Recognition and Interaction, Rostock, Germany, 16–17 September 2019.
  5. Bell, M.D.; Weinstein, A.J.; Pittman, B.; Gorman, R.M.; Abujelala, M. The Activate Test of Embodied Cognition (ATEC): Reliability, concurrent validity and discriminant validity in a community sample of children using cognitively demanding physical tasks related to executive functioning. Child Neuropsychol. 2021, 27, 973–983.
  6. Zheng, W.; Zhang, Q.-E.; Cai, D.-B.; Ng, C.H.; Ungvari, G.S.; Ning, Y.-P.; Xiang, Y.-T. Neurocognitive dysfunction in subjects at clinical high risk for psychosis: A meta-analysis. J. Psychiatr. Res. 2018, 103, 38–45.
  7. Carrión, R.E.; McLaughlin, D.; Goldberg, T.E.; Auther, A.M.; Olsen, R.H.; Olvet, D.; Correll, C.U.; Cornblatt, B.A. Prediction of functional outcome in individuals at clinical high risk for psychosis. JAMA Psychiatry 2013, 70, 1133–1142.
  8. Hofheinz, M.; Schusterschitz, C. Dual task interference in estimating the risk of falls and measuring change: A comparative, psychometric study of four measurements. Clin. Rehabil. 2010, 24, 831–842.
  9. Espay, A.J.; Bonato, P.; Nahab, F.B.; Maetzler, W.; Dean, J.M.; Klucken, J.; Eskofier, B.M.; Merola, A.; Horak, F.; Lang, A.E.; et al. Technology in Parkinson’s disease: Challenges and opportunities. Mov. Disord. 2016, 31, 1272–1282.
  10. Stroud, C.; Onnela, J.P.; Manji, H. Harnessing digital technology to predict, diagnose, monitor, and develop treatments for brain disorders. NPJ Digit. Med. 2019, 2, 44.
  11. Gold, M.; Amatniek, J.; Carrillo, M.C.; Cedarbaum, J.M.; Hendrix, J.A.; Miller, B.B.; Robillard, J.M.; Rice, J.J.; Soares, H.; Tome, M.B.; et al. Digital technologies as biomarkers, clinical outcomes assessment, and recruitment tools in Alzheimer’s disease clinical trials. Alzheimers Dement. 2018, 4, 234–242.
More
© Text is available under the terms and conditions of the Creative Commons Attribution (CC BY) license; additional terms may apply. By using this site, you agree to the Terms and Conditions and Privacy Policy.
This entry is offline, you can click here to edit this entry!
Video Production Service
Feedback