Tyler Nickle and Dr. Ramona Hopkins, Department of Psychology
Multiple sclerosis is a chronic inflammatory disease of the central nervous system. Studies show that 40-70% of individuals with MS have cognitive impairments in memory, executive functioning, attention, and processing speed (Rogers and Panegyres, 2007). Quantitative Electroencephalographic peak alpha frequency (PAF) is used to measure physiological markers of cognitive performance between healthy and clinical individuals. High peak alpha frequency is a measurement of spectral density within 8-12 Hz and has been associated with cognitive preparedness and may be an indicator of cognitive functioning (Angelakis and Lubar, 2004). This project attempts to describe the relationship between Quantitative Electroencephalographic (qEEG) peak alpha, and its relationship with scores on the PASAT, a test used to measure attention, working memory, and processing speed, in individuals with Multiple Sclerosis (MS).
In this study, subjects consisted of 9 females diagnosed with Relapse-Remitting Multiple Sclerosis and 9 age and sex-matched normal controls from a normative EEG database. MS subjects were recruited by a Board of Certified Neurologists (Dr. John F. Foley, MD) from the Rocky Mountain Neurological MS Clinic; 370 9TH Ave Ste. 106, Salt Lake City, UT 84103. The number of subjects recruited for this study was sufficient to draw correlations and some conclusions; however, the number of subjects was not as high as was hoped for; it was anticipated that 22-24 individuals would participate in this study. For this reason, further testing, in this area would be recommended. The EEG analysis consisted of 24 craniofacial electrodes that were applied to the persons scalp. QEEG was computed using the Neuroguide software package. Peak alpha frequency was calculated from eyes closed at rest EEG. Participants completed the Paced Auditory Serial Addition Task (PASAT) during QEEG. Fifty-nine pairs of digits are added for each of two trials, (presenting rates: 3.0s and 2.0s) beginning with the 3.0s trial first and progressing to the 2.0s trial. The PASAT score is calculated as total correct
responses per trial out of 59 possible correct responses.
What was found was that Relapse-remitting MS patients, who are those who begin to have progressive neurologic decline, had lower peak alpha frequency on qEEG on right frontal electrodes compared to controls that approached significance, but not at other sites. Zero-order correlations showed higher peak alpha frequency was associated with improved PASAT performance on both 3 and 2 second trials at frontal, central, temporal, and occipital electrode sites. Correlations were also between PASAT scored with peak alpha frequency for right frontal electrodes.
These results demonstrate that individuals with MS have diminished cognitive ability in the right frontal areas of their brain. This general area of the brain is associated with executive functioning, working memory, processing speed, and attention; and as mentioned above, the decline of these symptoms was the center of the hypothesis of this project. The overall objective of this study was to further define MS and to attempt to offer an accurate method for assessing the onset of this disorder. If MS is discovered during its earlier stages, it can be treated accordingly to slow the progression of the disorder providing a patient with a longer period of functionality. The findings presented here suggest that peak alpha frequency may be useful in identifying cognitive impairments in MS patients, and may also act as a tool when diagnosing MS. In order to further diagnose the onset of MS it is suggested that here that electroencephalographic event-related potential (ERP) correlations be studied; specifically, to est the relationship between ERP’s and attention, arousal, processing speed, and error monitoring. ERP’s are electrophysiological responses to an internal stimulus measured by EEG; these correlations would add another dimension and tactic in diagnosing MS.
- Angelakis, E., Lubar, J.F., & Stathopoulou, S. (2004). Electroencephalographic peak alpha frequency correlates of cognitive traits. Neuroscience Letters, 371, 60-63.
- Lassmann, H. (Ed.). (2008). Pathology of neurons in multiple sclerosis. Boston: Elsevier Academic Press.
- Rogers, J. M., & Panegyres, P. K. (2007). Cognitive impairment in multiple sclerosis: Evidence-based analysis and recommendations. Journal of Clinical Neuroscience, 14, 919-927.