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Abstract: Mental imagery generation is essential in the retrieval and storage of knowledge. Previous studies have indicated that the holistic properties of mental imagery generation can be evaluated more easily than the partial properties. However, the relationship between partial and holistic mental imagery generations has not been clearly demonstrated. To address this issue, we designed a task to investigate the changes in the spectrum of the electroencephalogram (EEG) during partial or holistic imagery generation. EEG signals were obtained from 18 healthy subjects, and a statistical measure of spectral dynamics between two EEG signals in per frequency band was performed. Additionally, a bicoherence spectrum analysis was used to detect the phase coupling within these two imagery conditions. Our results indicated that EEG of the partial imagery appeared earlier and stronger than that of the holistic imagery in the theta (5–8 Hz) range in a time window around 220 to 300 ms after cue onset, and a slight decrease in the alpha (8–12 Hz) band was observed at around 270 ms. The scalp topography of these changes in the theta and alpha bands distributed overall significantly in the frontal and central-temporal areas. The significant phase coupling within two conditions was remarkable at high frequency. From these results, we infer that there are complex relations between partial and holistic imageries. The generation of partial mental imagery is not a subprocess of holistic imagery, but it is relevant to holistic imagery and requires correct modification from the holistic information.

[1]Arnfred, S.M., Hansen, L.K., Parnas, J., Morup, M., 2008. Regularity increases middle latency evoked and late induced beta brain response following proprioceptive stimulation. Brain Res. Cogn. Brain Res., 1218:114-131.

[2]Borthwick, C.J., Crossley, R., 2004. Permanent vegetative state: usefulness and limits of a prognostic definition. NeuroRehabilitation, 19(4):381-389.

[3]Bruns, A., Eckhorn, R., 2004. Task-related coupling from high-to low-frequency signals among visual cortical areas in human subdural recordings. Int. J. Psychophysiol., 51(2):97-116.

[4]Caldwell, J.A., Prazinko, B., Caldwell, J.L., 2003. Body posture affects electroencephalographic activity and psychomotor vigilance task performance in sleep-deprived subjects. Clin. Neurophysiol., 114(1):23-31.

[5]Cornoldi, C., Rossana, D.B., 1998. Memory and Imagery: A Visual Trace is not a Mental Image. In: Martin, A.C., Susan, E.G., Cesare, C. (Eds.), Theories of Memory. Psychology Press, UK, p.87-110.

[6]de Beni, R., Pazzaglia, F., 1995. Memory for different kinds of mental images: role of contextual and autobiographic variables. Neuropsychologia, 33(11):1359-1371.

[7]Delorme, A., Makeig, S., 2004. An open source toolbox for analysis of single-trial EEG dyanmics including independent components analysis. J. Neurosci. Methods, 134(1):9-21.

[8]Farah, M.J., 1988. Is visual imagery really visual? Overlooked evidence from neuropsychology. Psychol. Rev., 95(3):307-317.

[9]Ganis, G., Thompson, W.L., Kosslyn, S.M., 2004. Brain areas underlying visual mental imagery and visual perception: an fMRI study. Cogn. Brain Res., 20(2):226-241.

[10]Jennett, B., Adams, J.H., Murray, L.S., Graham, D.I., 2001. Neuropathology in vegetative and severely disabled patients after head injury. Am. Acad. Neurol., 56(4):486-490.

[11]Jensen, O., Tesche, C.D., 2002. Frontal theta activity in humans increases with memory load in a working memory task. Eur. J. Neurosci., 15(8):1395-1399.

[12]Khateb, A., Abutalebi, J., Michel, C.M., Pegna, A.J., Lee-Jahnke, H., Annoni, J.M., 2007. Language selection in bilinguals: a spatio-temporal analysis of electric brain activity. Int. J. Psychophysiol., 65(3):201-213.

[13]Kosslyn, S.M., 1994. Image and Brain: The Resolution of the Imagery Debate. MIT Press, Cambridge, MA, p.516.

[14]Kotchoubey, B., Lang, S., Mezger, G., Schmalohr, D., Schneck, M., Semmler, A., Bostanov, V., Birbaumer, N., 2005. Information processing in severe disorders of consciousness: vegetative state and minimally conscious state. Clin. Neurophysiol., 116(10):2441-2453.

[15]Låg, T., Hveem, K., Puud, K.P.E., Laeng, B., 2006. The visual basis of category effects in object identification: evidence from the visual hemifield paradigm. Brain Cogn., 60(1):1-10.

[16]Leon-Carrion, J., Martin-Rodriguez, J.F., Damas-Lopez, J., Martin, J.M.B.Y., Dominguez-Morales, M.R., 2008. Brain function in the minimally conscious state: a quantitative neurophysiological study. Clin. Neurophysiol., 119(7):1506-1514.

[17]Li, X., Yao, X., Fox, J., Jefferys, J.G., 2007a. Interaction dynamics of neuronal oscillations analysed using wavelet transforms. J. Neurosci. Methods, 160(1):178-185.

[18]Li, X., Cui, D., Jiruska, P., Fox, J., Yao, X., Jefferys, J.G., 2007b. Synchronization measurement of multiple neuronal populations. J. Neurophysiol., 98(6):3341-3348.

[19]Liu, X., Qi, H., Wang, S.P., Wan, M.X., 2006. Wavelet-based estimation of EEG coherence during Chinese Stroop task. Comput. Biol. Med., 36(12):1303-1315.

[20]Macwhinney, B., Cohen, J., Provost, J., 1997. The PsyScope experiment-building system. Spat. Vis., 11(1):99-101.

[21]Mallat, S., 1999. A Wavelet Tour of Signal Processing. London Academic Press, San Diego, p.42-125.

[22]Min, B.K., Hermann, C.S., 2007. Prestimulus EEG alpha activity reflects prestimulus top-down processing. Neurosci. Lett., 422(2):131-135.

[23]Min, B.K., Park, J.Y., Kim, E.J., Kim, J.I., Kim, J.J., Park, H.J., 2008. Prestimulus EEG alpha activity reflects temporal expectancy. Neurosci. Lett., 438(3):270-274.

[24]Peterson, M.A., Kihlstrom, J.F., Rose, P.M., Glisky, M.L., 1992. Mental images can be ambiguous: reconstruals and reference-frame reversals. Mem. Cognit., 20(2):107-123.

[25]Qiu, J., Li, H., Liu, Q., Zhang, Q.L., 2007. Brain mechanisms underlying visual perception and visual mental imagery of Chinese pseudo-characters: an event-related potential study. Brain Res. Cogn. Brain Res., 1184:202-209.

[26]Rouw, R., Kosslyn, S.M., Hamel, R., 1997. Detecting high-level and low-level properties in visual images and visual percepts. Cognition, 63(2):209-226.

[27]Shepard, R.N., Cooper, L.A., 1982. Mental Images and Their Transformations. MIT Press, Cambridge, MA, p.325-340.

[28]Srinivasan, N., 2007. Cognitive neuroscience of creativity: EEG based approaches. Methods, 42(1):109-116.

[29]Thomas, R., Forde, E., 2006. The role of local and global processing in the recognition of living and nonliving things. Neuropsychologia, 44(6):982-986.

[30]Tippett, L.J., 1992. The generation of visual images: a review of neuropsychological research and theory. Psychol. Bull., 112(3):415-432.

[31]von Stein, A., Sarnthein, J., 2000. Different frequencies for different scales of cortical integration: from local gamma to long range alpha/theta synchronization. Int. J. Psychophysiol., 38(3):301-313.