Neural Signals of Cognition During Computer Use

Alan Gevins

SAM Technology

CONTACT INFORMATION

SAM Technology
101 Spear St.; Ste. 203
San Francisco, CA 94105
Phone: (415) 227-4900
Fax : (415) 546-7122
Email: alan@eeg.com

PROGRAM AREA

Usability and User-Centered Design

KEYWORDS

Human-computer interface evaluation, index of mental effort, brainwave monitor.

PROJECT SUMMARY

We are developing an enabling technology to monitor brain signals of mental effort while people work at a computer. Among other applications, this technology will help in objectively evaluating the ease of use of computer interfaces in order to optimize interfaces to the needs of their human users. The first objective of the project was to demonstrate that valid measures of cognitive brain utilization could be extracted from electric potential recordings taken at the human scalp (electroencephalograms, EEGs) during computer-based work. Having initially met this objective, we plan to perform an experiment in which the technology is used to evaluate the cognitive load experienced by novice and expert programmers during the act of programming.

PROJECT REFERENCES

Gevins, A., Smith, M.E., Leong, H., McEvoy, L., Whitfield, S., Du, R., & Rush, G. (In Press). Monitoring working memory load during computer-based tasks with EEG pattern recognition. Human Factors.

Gevins, A., Smith, M.E., McEvoy, L., & Yu, D. (1997). High resolution EEG mapping of cortical activation related to working memory. Cerebral Cortex, 7, 374-385 .

Gevins, A.S. (1996). Electrophysiological imaging of brain function. (pp. 259-276). In: Toga, A.W. and Mazziotta, J.C (Eds). Brain Mapping: The Methods. Academic Press: San Diego.

Gevins, A.S., Smith, M.E., Le, J., Leong, H., Bennett, J., Martin, N., McEvoy, L., Du., R., & Whitfield, S. (1996) High resolution evoked potential imaging of the cortical dynamics of human working memory. Electroencephalography and Clinical Neurophysiology, 98, 327-348.

Gevins, A., Leong, H., & Smith, M.E., Le, J. & Du, R. (1995). Mapping cognitive brain function with modern high resolution electroencephalography. Trends in Neurosciences, 18, 429-436.

AREA BACKGROUND

The main focus of our laboratory is on the discipline of cognitive neurophysiology. Cognitive neurophysiology is the study of changes in brain function and the relationship of such changes to thought processes. The primary physiological signal that we measure is the electroencephalogram or EEG. The EEG reflects summated potentials generated by the electrochemical signaling processes by which networks of neurons process information. The EEG changes in predictable ways as a function of level of alertness, type and/or intensity of mental activity, and particular forms of brain pathology. We record the EEG by arrays of electrodes attached with conductive gel to many locations across the scalp. Similar sensors are attached to the face in the region of the eyes to record the electro-oculogram or EOG, that is, the electrical potentials generated by eye movements and blinks. The EOG can also provide useful information about mental state.

Our overall research effort within this discipline is fairly broad. On the one hand, our laboratory is best known for engineering methodological advances in EEG analysis, and applying those advances in basic research studies of higher brain function. On the other hand, we also have a history of performing research on both clinical issues and human factors problems. As noted in the project summary, in recent years we have been developing and evaluating methods for monitoring mental effort during computer-based work. During this effort significant signal processing problems have been addressed, including dissociating electrical potentials generated by the brain from those generated by the eyes and muscles, and identifying the particular parameters of the constituent electrical signals that most closely and reliably index mental effort. A related engineering problem has involved implementing a system for EEG recording and near real-time signal extraction and analysis. These efforts have resulted in a feasibility demonstration technology that is capable of monitoring mental effort during naturalistic computer-based activities. We are currently performing pilot experiments utilizing this system, and planning improvements to it.

AREA REFERENCES

Gevins, A.S., Leong, H., Du, R., Smith, M.E., Le, J., DuRousseau, D., Zhang, J., & Libove, J. (1995). Towards measurement of brain function in operational environments. Biological Psychology, 40, 169-186.

Gevins, A.S., and Cutillo, B.A. (1995). Neuroelectric measures of the mind. In: P.L. Nunez (Ed.), Neurocortical Dynamics and Human EEG Rhythms, Oxford University Press: New York, pp. 304-388.

Kramer, A.F., Trejo, L.J. & Humphrey, D.G. (1996). Psychophysiological measures of workload: Potential applications to adaptively automated systems. In R. Parasuraman & M. Mouloua (Eds), Automation and Human Performance, Lawrence Erlbaum Associates, Mahwah, New Jersey, pp. 137-162.

Parasuraman, R. (1990). Event-related brain potentials and human factors research. In J. W. Rohrbaugh, R. Parasuraman, R. J. Johnson (Ed.), Event-Related Brain Potentials, (pp. 279-300). New York: Oxford University Press.

Wilson, G. F. & Fisher, F. (1995). Cognitive task classification based upon topographic EEG data. Biological Psychology, 40, 239-250.

RELATED PROGRAM AREAS

Adaptive Human Interfaces.

POTENTIAL RELATED PROJECTS

We would like to collaborate with a team working on adaptive interfaces.