Advertisement

Evaluation of Cognitive Control and Distraction Using Event-Related Potentials in Healthy Individuals and Patients with Multiple Sclerosis

  • Thomas J. CoveyEmail author
  • Janet L. Shucard
  • David W. Shucard
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9743)

Abstract

Multiple Sclerosis (MS) is a disorder of the central nervous system that can result in cognitive dysfunction. Despite the prevalence of cognitive impairments in MS, few studies have directly examined dysfunction in the domain of cognitive control, which involves the monitoring of conflicting stimulus input and response options and the subsequent selection of an appropriate response (and inhibition of inappropriate responses). The present study examined event-related potential (ERP) indices of brain function in MS patients and healthy controls (HCs) for a Go/Nogo Flanker task of cognitive control. The task required participants to respond appropriately to a central target arrow stimulus that was flanked by non-target stimuli that were congruent, incongruent, or neutral with respect to the target. On some trials, a two-sided target arrow was presented, which required the inhibition of a response (Nogo). The Nogo stimulus also was surrounded by flankers (arrow primes or neutral). MS patients had slower reaction times during Go trials compared to HCs. Patients exhibited prolonged latencies for P1, frontal P2, N2, and P3 components compared to HCs. MS patients, compared to HCs, also had a more pronounced anteriorization for P3 amplitude during Nogo compared to Go trials, possibly indicating inhibitory dysfunction. Finally, decreased amplitude was also observed in MS patients compared to HCs for a positive-negative complex with very early latency onset, which may reflect dysfunction in early processing of the flanker stimuli. The findings indicate dysfunction at multiple stages of processing in MS patients during cognitive control.

Keywords

Cognitive control Inhibition Multiple sclerosis ERPs 

Notes

Acknowledgements

This study was supported by pilot research grant PP2249 from the National Multiple Sclerosis Society and by a University at Buffalo Mark Diamond Research Fund Graduate Student Grant.

References

  1. 1.
    Cercignani, M., Iannucchi, G., Rocca, M.A., Comi, G., Horsfield, M.A., Filippi, M.: Pathologic damage in MS assessed by diffusion-weighted magnetization transfer MRI. Neurology 54, 1139–1144 (2000)CrossRefGoogle Scholar
  2. 2.
    Kutzelnigg, A., Lucchinetti, C.F., Stadelmann, C., Bruck, W., Rauschka, H., Bergmann, M., Shmidbauer, M., Parisi, J.E., Lassmann, H.: Cortical demyelination and diffuse white matter injury in multiple sclerosis. Brain 128, 2705–2712 (2005)CrossRefGoogle Scholar
  3. 3.
    Sanfilipo, M.P., Benedict, R.H.B., Sharma, J., Weinstock-Guttman, B., Backshi, R.: The relationship between whole brain volume and disability in multiple sclerosis: a comparison of normalized gray vs. white matter with misclassification correction. NeuroImage 26, 1068–1077 (2005)CrossRefGoogle Scholar
  4. 4.
    Chiaravalloti, N.D., DeLuca, J.: Cognitive impairment in multiple sclerosis. Lancet Neurol. 7, 1139–1151 (2008)CrossRefGoogle Scholar
  5. 5.
    Covey, T.J., Zivadinov, R., Shucard, J.L., Shucard, D.W.: Information processing speed, neural efficiency, and working memory performance in Multiple Sclerosis: Differential relationships with structural magnetic resonance imaging. J. Clin. Exp. Neuropsychol. 33, 1129–1145 (2011)CrossRefGoogle Scholar
  6. 6.
    Lazeron, R.H.C., Boringa, J.B., Schouten, M., Uitdehaag, B.M.J., Bergers, E., Lindeboom, J., Eikelenboom, M.J., Scheltens, P.H., Barkhof, F., Polman, C.H.: Brain atrophy and lesion load as explaining parameters for cognitive impairment in multiple sclerosis. Multiple Sclerosis 11, 524–531 (2005)CrossRefGoogle Scholar
  7. 7.
    Sacco, R., Bisecco, A., Corbo, D., Della Corte, M., d’Ambrosio, A., Docimo, R., Gallo, A., Esposito, F., Esposito, S., Cirillo, M., Lovorgna, L., Tedeschi, G., Bonavita, S.: Cognitive impairment and memory disorders in relapsing-remitting multiple sclerosis: the role of white matter, gray matter, and hippocampus. J. Neurol. 262, 1691–1697 (2015)CrossRefGoogle Scholar
  8. 8.
    Sanfilipo, M.P., Benedict, R.H.B., Weinstock-Gutmann, B., Bakshi, R.: Gray and white matter brain atrophy and neuropsychological impairment in multiple sclerosis. Neurology 66, 685–692 (2006)CrossRefGoogle Scholar
  9. 9.
    Huster, R.J., Enriquez-Geppert, S., Lavallee, C.F., Falkenstein, M., Herrmann, C.S.: Electroencephalography of response inhibition tasks: functional networks and cognitive contributions. Int. J. Psychophysiol. 87, 217–233 (2013)CrossRefGoogle Scholar
  10. 10.
    Groom, M.J., Cragg, L.: Differential modulation of the N2 and P3 event-related potentials by response conflict and inhibition. Brain Cogn. 97, 1–9 (2015)CrossRefGoogle Scholar
  11. 11.
    Kopp, B., Mattler, U., Goertz, R., Rist, F.: N2, P3 and the lateralized readiness potential in a nogo task involving selective response priming. Electroencephalogr. Clin. Neurophysiol. 99, 19–27 (1996)CrossRefGoogle Scholar
  12. 12.
    Shaurya Prakash, R., Erickson, K.I., Snook, E.M., Colcombe, S.J., Motl, R.W., Kramer, A.F.: Cortical recruitment during selective attention in multiple sclerosis: an fMRI investigation of individual differences. Neuropsychologia 46, 2888–2895 (2008)CrossRefGoogle Scholar
  13. 13.
    Lopez-Gongora, M., Escartin, A., Martinez-Horta, S., Fernandez-Bobadilla, R., Querol, L., Romero, S., Angel Mananas, M., Riba, J.: Neurophysiological evidence of compensatory brain mechanisms in early-stage multiple sclerosis. PLoS ONE 10, e0136786 (2015)CrossRefGoogle Scholar
  14. 14.
    Uttl, B.: North American adult reading test: age norms, reliability, and validity. J. Clin. Exp. Neuropsychol. 24, 1123–1137 (2002)CrossRefGoogle Scholar
  15. 15.
    Polman, C.H., Reingold, S.C., Banwell, B., Clanet, M., Cohen, J.A., Filippi, M., et al.: Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann. Neurol. 69, 292–302 (2011)CrossRefGoogle Scholar
  16. 16.
    Covey, T.J., Shucard, J.L., Violanti, J.M., Lee, J., Shucard, D.W.: The effects of exposure to traumatic stressors on inhibitory control in police officers: a dense electrode array study using a Go/NoGo continuous performance task. Int. J. Psychophysiol. 87, 363–375 (2013)CrossRefGoogle Scholar
  17. 17.
    Fonaryova Key, A.P., Dove, G.O., Maguire, M.J.: Linking brainwaves to the brain: an ERP primer. Dev. Neuropsychol. 27, 183–215 (2005)CrossRefGoogle Scholar
  18. 18.
    Kopp, B., Rist, F., Mattler, U.: N200 in the flanker task as a neurobehavioral tool for investigating executive control. Psychophysiology 33, 282–294 (1996)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Thomas J. Covey
    • 1
    Email author
  • Janet L. Shucard
    • 1
  • David W. Shucard
    • 1
  1. 1.Division of Cognitive and Behavioral Neurosciences, Department of Neurology, Neuroscience Program, The Jacobs School of Medicine and Biomedical SciencesUniversity at Buffalo, State University of New YorkBuffaloUSA

Personalised recommendations