A primary model of decoherence in neuronal microtubules based on the interaction Hamiltonian between microtubules and plasmon in neurons
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摘要
Microtubules(MTs) are part of the cellular cytoskeleton and they play a role in many activities, such as cell division and maintenance of cell shape. In recent years, MTs have been thought to be involved in storing and processing information.Several models have been developed to describe the information-processing ability of MTs. In these models, MTs are considered as a device that can transmit quantum information. However, MTs are affected by the "wet and warm" cellular environment, thus it is essential to calculate the decoherence time. Many researchers have attempted to calculate this parameter but the values that have been obtained vary markedly. Previous studies considered the cellular environment as a distant ion; however, this treatment is somewhat simplified. In this study, we develop a model to determine the decoherence time in neuronal MTs while considering the interaction effects of the neuronal fluid environment. The neuronal environment is considered as a plasmon reservoir. The coupling between MTs and neuronal environment occurs due to the interaction between dipoles and plasmon. The interaction Hamiltonian is derived by using the second quantization method, and the coupling coefficient is calculated. Finally, the decoherence time scale is estimated according to the interaction Hamiltonian.In this paper, the time scale of decoherence in MTs is approximately 1 fs-100 fs. This model may be used as a reference in other decoherence processes in biological tissues.
Microtubules(MTs) are part of the cellular cytoskeleton and they play a role in many activities, such as cell division and maintenance of cell shape. In recent years, MTs have been thought to be involved in storing and processing information.Several models have been developed to describe the information-processing ability of MTs. In these models, MTs are considered as a device that can transmit quantum information. However, MTs are affected by the "wet and warm" cellular environment, thus it is essential to calculate the decoherence time. Many researchers have attempted to calculate this parameter but the values that have been obtained vary markedly. Previous studies considered the cellular environment as a distant ion; however, this treatment is somewhat simplified. In this study, we develop a model to determine the decoherence time in neuronal MTs while considering the interaction effects of the neuronal fluid environment. The neuronal environment is considered as a plasmon reservoir. The coupling between MTs and neuronal environment occurs due to the interaction between dipoles and plasmon. The interaction Hamiltonian is derived by using the second quantization method, and the coupling coefficient is calculated. Finally, the decoherence time scale is estimated according to the interaction Hamiltonian.In this paper, the time scale of decoherence in MTs is approximately 1 fs-100 fs. This model may be used as a reference in other decoherence processes in biological tissues.
Microtubules(MTs) are part of the cellular cytoskeleton and they play a role in many activities, such as cell division and maintenance of cell shape. In recent years, MTs have been thought to be involved in storing and processing information.Several models have been developed to describe the information-processing ability of MTs. In these models, MTs are considered as a device that can transmit quantum information. However, MTs are affected by the "wet and warm" cellular environment, thus it is essential to calculate the decoherence time. Many researchers have attempted to calculate this parameter but the values that have been obtained vary markedly. Previous studies considered the cellular environment as a distant ion; however, this treatment is somewhat simplified. In this study, we develop a model to determine the decoherence time in neuronal MTs while considering the interaction effects of the neuronal fluid environment. The neuronal environment is considered as a plasmon reservoir. The coupling between MTs and neuronal environment occurs due to the interaction between dipoles and plasmon. The interaction Hamiltonian is derived by using the second quantization method, and the coupling coefficient is calculated. Finally, the decoherence time scale is estimated according to the interaction Hamiltonian.In this paper, the time scale of decoherence in MTs is approximately 1 fs-100 fs. This model may be used as a reference in other decoherence processes in biological tissues.
引文
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[41]Trocha P,Karpov M,Ganin D,Pfeiffer M H,Kordts A,Wolf S,Krockenberger J,Marin-Palomo P,Weimann C and Randel S 2018 Science359 887
[2]Franco M I and Siddiqi O 2011 Proc.Natl.Acad.Sci.USA 108 3797
[3]Ritz T,Adem S and Schulten K 2000 Biophys.J.78 707
[4]Hiscock H G,Worster S,Kattnig D R,Steers C,Jin Y,Manolopoulos D E,Mouritsen H and Hore P J 2016 Proc.Natl.Acad.Sci.USA 113201600341
[5]Gregory S E,Tessa R C,Elizabeth L R,Tae-Kyu A,Tom′as M,YuanChung C,Robert E B and Graham R F 2007 Nature 446 782
[6]Romero E,Augulis R,Novoderezhkin V I,Ferretti M,Thieme J,Zigmantas D and Van Grondelle R 2014 Nat.Phys.10 676
[7]Levi F,Mostarda S,Rao F and Mintert F 2015 Rep.Prog.Phys.78082001
[8]Novelli F,Nazir A,Richards G H,Roozbeh A,Wilk K E,Curmi P Mand Davis J A 2015 J.Phys.Chem.Lett.6 4573
[9]Sarovar M,Ishizaki A,Fleming G and Whaley B 2010 Nat.Phys.3 462
[10]Marletto C,Coles D,Farrow T and Vedral V 2018 J.Phys.Commun.2101001
[11]Mesquita M V,Vasconcellos′A R,Luzzi R and Mascarenhas S 2005Int.J.Quantum Chem.102 1116
[12]Jackendoff R 1987 Consciousness and the Computational Mind(Cambridge:The MIT Press)pp.275-280
[13]Tononi G,Boly M,Massimini M and Koch C 2016 Nat.Rev.Neurosci.17 450
[14]Crick F and Koch C 2003 Nat.Neurosci.6 119
[15]Edelman G M 2003 Proc.Natl.Acad.Sci.USA 100 5520
[16]Jahn R G and Dunne B J 2007 Found.Phys.3 306
[17]Mershin A,Sanabria H,Miller J H,Nawarathna D,Skoulakis E M,Mavromatos N E,Kolomenskii A A,Schuessler H A,Luduena R Fand Nanopoulos D V 2006 The Emerging Physics of Consciousness(Berlin:Springer)pp.95-170
[18]Hameroff S and Penrose R 2014 Phys.Life Rev.11 39
[19]Hameroff S and Penrose R 2014 Phys.Life Rev.11 94
[20]Hameroff S R and Penrose R 2017 Biophysics of Consciousness:AFoundational Approach(Singapore:World Scientific)pp.517-599
[21]Craddock T J A and Tuszynski J A 2010 J.Biol.Phys.36 53
[22]Craddock T J,Priel A and Tuszynski J A 2014 J.Integr.Neurosci.13293
[23]Fisher M 2015 Ann.Phys.61 593
[24]Hameroff S R 2007 Cogn.Sci.31 1035
[25]Mavromatos N E,Mershin A and Nanopoulos D V 2002 Int.J.Mod.Phys.B 16 3623
[26]Mavromatos N 1999 Bioelectrochemistry Bioenergetics 48 273
[27]Tegmark M 2000 Phys.Rev.E 61 4194
[28]Hagan S,Hameroff S R and Tuszy′nski J A 2002 Phys.Rev.E 65061901
[29]Nelson P 2007 Biological Physics(New York:WH Freeman)p.416
[30]Priel A,Tuszynski J A and Woolf N J 2005 Eur.Biophys.J.Biophys.Lett.35 40
[31]Privman V and Tolkunov D 2005 Quantum Information and Computation III(Bellingham:The International Society for Optics and Photonics),pp.187-195
[32]Tolkunov D,Privman V and Aravind P K 2005 Phy.Rev.A 71 060308
[33]Craddock T J,Friesen D,Mane J,Hameroff S and Tuszynski J A 2014J.R.Soc.Interface 11 20140677
[34]Chen Y,Okur H I,Gomopoulos N,Macias-Romero C,Cremer P S,Petersen P B,Tocci G,Wilkins D M,Liang C and Ceriotti M 2016 Sci.Adv.2 e1501891
[35]Frohlich H 1968 Int.J.Quantum Chem.2 641
[36]Wu T M and Austin S J 1981 J.Biol.Phys.9 97
[37]Bohm D and Pines D 1953 Phy.Rev.92 609
[38]Yin C C and Biophysics D O 2018 Chin.Phys.B 27 058703
[39]Zheng C J,Jia T Q,Zhao H,Xia Y J,Zhang S A and Sun Z R 2018Chin.Phys.B 27 057802
[40]Wade C G,Sibalic N,de Melo N R,Kondo J M,Adams C S and Weatherill K J 2017 Nat.Photon.11 40
[41]Trocha P,Karpov M,Ganin D,Pfeiffer M H,Kordts A,Wolf S,Krockenberger J,Marin-Palomo P,Weimann C and Randel S 2018 Science359 887