Abstract
Building a real artificial intelligence system is a big dream for human for many years. One of the main problems is that we do not have a good indicator to measure the conscious level both for biological system and human-made system. To solve this problem, we combined the method of human-made communication system (Radio system) and the major idea about the biological origin of consciousness, namely, the corporation of a huge number of neurons. And we proposed an approximate indicator: the frequencies of the spontaneous activity - very low frequency oscillation (vLFO ~0.03 Hz) and low frequency oscillation (LFO ~0.18 Hz). The results showed that the vLFO became faster and the LFO stayed consistent when the brain changed into a lower conscious level. Thus, we may probably try to build a bionic brain by combining this phenomena and other conclusion.
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References
LeCun, Y., Bengio, Y., Hinton, G.: Deep learning. Nature 521, 436–444 (2015)
Litjens, G., et al.: A survey on deep learning in medical image analysis. Med. Image Anal. 42, 60–88 (2017)
Mnih, V., et al.: Human-level control through deep reinforcement learning. Nature 518, 529 (2015)
Miller, G., et al.: What is the biological basis of consciousness? Science 309, 79–102 (2005)
Dehaene, S., Lau, H., Kouider, S.: What is consciousness, and could machines have it? Science 358, 486 (2017)
Heit, E.: Brain imaging, forward inference, and theories of reasoning. Front. Hum. Neurosci. 8, 1056 (2014)
Dehaene, S.: The eternal silence of neuronal spaces. Science 336, 1507 (2012)
Li, M., Liu, Y.D.: Spatio-temporal analysis of stimuli-modulated spontaneous low frequency oscillations. Chin. Sci. Bull. 52, 1475–1483 (2007)
Hirschberg, H., et al.: Hemodynamic low-frequency oscillation reflects resting-state neuronal activity in rodent brain, vol. 9305, p. 930517 (2015)
Horikawa, T., Tamaki, M., Miyawaki, Y., Kamitani, Y.: Neural decoding of visual imagery during sleep. Science 340, 639–642 (2013)
Astashev, M.E., Serov, D.A., Tankanag, A.V.: Anesthesia effects on the low frequency blood flow oscillations in mouse skin. Ski. Res. Technol. 25, 40–46 (2018)
Mitra, A., et al.: Spontaneous infra-slow brain activity has unique spatiotemporal dynamics and laminar structure. Neuron 98, 297–305 (2018)
Shih, A.Y., Driscoll, J.D., Drew, P.J., Nishimura, N., Schaffer, C.B., Kleinfeld, D.: Two-photon microscopy as a tool to study blood flow and neurovascular coupling in the rodent brain. J. Cereb. Blood Flow Metab. 32, 1277–1309 (2012)
Kouider, S., et al.: A neural marker of perceptual consciousness in infants. Science 340, 376–380 (2013)
Winder, A.T., Echagarruga, C., Zhang, Q., Drew, P.J.: Weak correlations between hemodynamic signals and ongoing neural activity during the resting state. Nat. Neurosci. 20, 1761–1769 (2017)
Huang, L., Liu, Y., Li, M., Hu, D.: Hemodynamic and electrophysiological spontaneous low-frequency oscillations in the cortex: directional influences revealed by Granger causality. Neuroimage 85, 810–822 (2014)
Huang, L., Liu, Y., Gui, J., Li, M., Hu, D.: Stimulus-dependent modulation of spontaneous low-frequency oscillations in the rat visual cortex. NeuroReport 25, 823–828 (2014)
Fox, M.D., Raichle, M.E.: Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nat. Rev. Neurosci. 8, 700–711 (2007)
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This work was supported by the National Science Foundation of China (61420106001).
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Li, F., Jiao, C., Li, M., Hu, D. (2019). A Measure of the Consciousness Revealed by the Cerebral Cortex Spontaneous Activity. In: Sun, F., Liu, H., Hu, D. (eds) Cognitive Systems and Signal Processing. ICCSIP 2018. Communications in Computer and Information Science, vol 1006. Springer, Singapore. https://doi.org/10.1007/978-981-13-7986-4_16
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DOI: https://doi.org/10.1007/978-981-13-7986-4_16
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