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Abstract: Objective: The functional relationship between calculated alpha band spectral power and inter-/intra-hemispheric coherence during a three-level working memory task of patients with mild cognitive impairment (MCI) was investigated. Methods: Subjects included 35 MCI patients according to the DSM-IV criteria (mean age: 62.3, SD: 6.5) and 34 healthy controls (mean age: 57.4, SD: 4.0) were selected from the community at large. All subjects performed a simple calculation and recall task with three levels of working memory load while electroencephalograph (EEG) signal was recorded. The spectral EEG power was computed over alpha1 (8.0~10.0 Hz) and alpha2 (10.5~13.0 Hz) frequency bands and was compared between rest stage and working memory processing stage by two-way ANOVA. Post hoc testing analyzed the differences between each two levels of working memory load during task processing. The inter-hemisphere EEG coherence of frontal (F3-F4), central (C3-C4), parietal (P3-P4), temporal (T5-T6) as well as occipital (O1-O2) was compared between MCI patients and normal controls. The EEG signals from F3-C3, F4-C4, C3-P3, C4-P4, P3-O1, P4-O2, T5-C3, T6-C4, T5-P3 and T6-P4 electrode pairs resulted from the intra-hemispheric action for alpha1 and alpha2 frequency bands. Result: There was significantly higher EEG power from MCI patients than from normal controls both at rest and during working memory processing. Significant differences existed between rest condition and three-level working memory tasks (P<0.001). The inter- and intra-hemispheric coherence during working memory tasks showed a “drop to rise” tendency compared to that at rest condition. There was significantly higher coherence in MCI patients than in the controls. When task difficulties increased, the cortical connectivity of intra-hemispheric diminished while the inter-hemispheric connectivity dominantly maintained the cognitive processing in MCI patients. Conclusion: The results of the present study indicate that the alpha frequency band may be the characteristic band in distinguishing MCI patients from normal controls during working memory tasks. MCI patients exhibit greater inter-hemispheric connectivity than intra-hemispheric connectivity when memory demands increase. MCI patients mobilize a compensatory mechanism to maintain the processing effectiveness while the processing efficiency is reduced.

[1] American Psychiatric Association, 1994. Diagnostic and Statistical Manual of Mental Disorders, 4th Ed. (DSM-IV). APA Press, Washington, DC.

[2] deToledo-Morrell, L., Evers, S., Hoeppner, T.J., Morrell, F., Garron, D.C., Fox, J.H., 1991. A ‘stress’ test for memory dysfunction. Electrophysiogical manifestation of early Alzheimer’s disease. Arch. Neurol., 48(6):605-609.

[3] Fink, A., Grabner, R.H., Neuper, C., Neubauer, A.C., 2005. EEG alpha band dissociation with increasing task demands. Cogn. Brain Res., 24(2):252-259.

[4] Folstein, M.F., Folstein, S.E., McHugh, P.R., 1975. “Mini-Mental State”. A practical method for grading the cognitive state of patients for the clinician. J. Psychiatr. Res., 12(3):189-198.

[5] Gevins, A., Smith, M.E., 2000. Neurophysiological measures of working memory and individual differences in cognitive ability and cognitive style. Cereb. Cortex, 10(9):829-839.

[6] Hebert, R., Lehmann, D., Tan, G., 2005. Enhanced EEG alpha time domain phase synchrony during transcendental meditation: implications for cortical integration theory. Signal Processing, 85(11):2213-2232.

[7] Hogan, M.J., Swanwick, G.R.J., Kaiser, J., Rowman, M., Lawlor, B., 2003. Memory-related EEG power and coherence reduction in mild Alzheimer’s disease. Int. J. Psychophysiol., 49(2):147-163.

[8] Hughes, C.P., Berg, L., Danziger, W.L., Coben, L.A., Martin, R.A., 1982. A new clinical scale for the staging of dementia. Br. J. Psychiatry, 140:566-572.

[9] Jensen, O., Gelfand, J., Kounios, J., Lisman, J.E., 2002. Oscillations in the alpha band (9~12 Hz) increase with memory load during retention in a short-term memory task. Cereb. Cortex, 12(8):877-882.

[10] Jiang, Z.Y., 2004. Research of diagnosis of Alzheimer’s disease based on coherence analysis of EEG signal. Chinese Journal of Sensor and Actuator, 17(3):363-366 (in Chinese).

[11] Jiang, Z.Y., 2005. Abnormal cortical functional connections in Alzheimer’s disease: analysis of inter- and intra-hemispheric EEG coherence. J. Zhejiang Univ. Sci., 6B(4):259-264.

[12] Jiang, Z.Y., Zheng, L.L., 2006. Inter- and intra-hemipheric EEG coherence in patients with mild cognitive impairement at rest and during working memory task. J. Zhejiang Univ. Sci., 7B(5):357-364.

[13] Jing, H., Takigawa, M., 2000. Observation of EEG coherernce after repetitive transcranial magnetic stimulation. Clin. Neurophysiol., 111(9):1620-1631.

[14] Klimesch, W., 1999. EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis. Brain Res. Rev., 29(2-3):169-195.

[15] Klimesch, W., Doppelmayr, M., Pachinger, T., Ripper, B., 1997. Brain oscillations and human memory: EEG correlates in the upper alpha and theta band. Neurosci. Lett., 238(1-2):9-12.

[16] Klimesch, W., Doppelmayr, M., Stadler, W., Pöllhuber, D., Sauseng, P., Röhm, D., 2001. Episodic retrieval is reflected by a process specific increase in human electro-encephalographic theta activity. Neurosci. Lett., 302(1):49-52.

[17] Lawton, W.P., Brody, M.P., 1969. Assessment of older people self-maintaining and instrumental activities of daily living. Gerontologist, 9:176-186.

[18] Petersen, R.C., Smith, G.E., Waring, S.C., Ivnic, R.J., Tangalos, E.G., Kokmen, E., 1999. Mild cognitive impairment: clinical characterization and outcome. Arch. Neurol., 56(3):303-308.

[19] Petersen, R.C., Doody, R., Kurz, A., Mohs, R.C., Morris, J.C., Rabins, P.V., Ritchie, K., Rossor, M., Thal, L., Winblad, B., 2001. Current concepts in mildcognitive impairment. Arch. Neurol., 58(12):1985-1992.

[20] Pijnenburg, Y.A.L., Made, Y., Knol, D.L., van Cappellen van Walsum, A.M., Knol, D.L., Scheltens, P., Stam, C.J., 2004. EEG synchronization likelihood in mild cognitive impairment and Alzheimer’s disease during a working memory task. Clin. Neurophysiol., 115(6):1332-1339.

[21] Reisberg, B., 1988. Functional assessment staging (FAST). Psychopharmacal. Bull, 24(4):653-659.

[22] Salthouse, T.A., Babcock, R.L., 1991. Decomposing adult age difference in working memory. Developmental Psychology, 27(5):763-776.

[23] Schürmann, M., Başar, E., 2001. Functional aspects of alpha oscillations in the EEG. Int. J. Psychophysiol., 39(2-3):151-158.

[24] Stam, C.J., 2000. Brain dynamics in theta and alpha frequency bands and working memory performance in humans. Neurosci. Lett., 286(2):115-118.

[25] Sternberg, S., 1969. Memory-scanning: mental processes revealed by reaction-time experiments. Am. Sci., 57(4):421-457.

[26] Suffczynski, P., Kalitzin, S., Pfurtscheller, G., Lopes da Silva, F.H., 2001. Computational model of thalamo-cortical networks: dynamical control of alpha rhythms in relation to focal attention. Int. J. Psychophysiol., 43(1):25-40.

[27] Weiss, S., Rappelsberger, P., 2000. Long-range EEG synchronization during word encoding correlates with successful memory performance. Cogn. Brain Res., 9(3):299-312.