Journal of Integrative Neuroscience, Vol. 13, No. 2 (2014) 293–311 c Imperial College Press ° DOI: 10.1142/S0219635214400019 Keeping time: Could quantum beating in microtubules be the basis for the neural synchrony related to consciousness? Travis J. A. Craddock Center for Psychological Studies Graduate School of Computer and Information Sciences College of Osteophatic Medicine and the Institute for Neuro-Immune Medicine Nova Southeastern University Fort Lauderdale, Florida 33314-7796, USA tcraddock@nova.edu Avner Priel The Israel Institute for Advanced Studies (IIAS) The Hebrew University of Jerusalem Edmond J. Safra, Givat Ram Campus Jerusalem, Israel 91904 Department of Physics, University of Alberta Edmonton, Alberta T6G 2E1, Canada apriel@ualberta.ca Jack A. Tuszynski* Department of Experimental Oncology Cross Cancer Institute Edmonton, Alberta T6G 1Z2, Canada Department of Physics, University of Alberta Edmonton, Alberta T6G 2E1, Canada jackt@ualberta.ca [Received 10 April 2014; Accepted 10 April 2014; Published 9 July 2014] This paper discusses the possibility of quantum coherent oscillations playing a role in neuronal signaling. Consciousness correlates strongly with coherent neural oscillations, however the mechanisms by which neurons synchronize are not fully elucidated. Recent experimental evidence of quantum beats in light-harvesting complexes of plants (LHCII) and bacteria provided a stimulus for seeking similar e®ects in important structures found in animal cells, especially in neurons. We argue that microtubules (MTs), which play critical roles in all eukaryotic cells, possess structural and functional characteristics that are consistent with quantum coherent excitations in the aromatic groups of their tryptophan residues. Furthermore we outline the consequences of these ¯ndings on neuronal processes including the emergence of consciousness. *Corresponding author. 293 294 T. J. A. CRADDOCK, A. PRIEL & J. A. TUSZYNSKI Keywords: Consciousness; neural synchrony; microtubules; quantum coherence; quantum biology. 1. The Problem of Consciousness Consciousness remains the most elusive and enigmatic problem for empirical science. De¯nition of the phenomenon is di±cult at best. There have been numerous attempts to describe consciousness in spiritual, philosophical and even scienti¯c terms, and while some of the de¯nitions agree across disciplines, others are at complete odds with one another. In general, however, it is accepted that consciousness is the condition of being aware of one's surroundings and one's own existence, or self-awareness (Tuszynski & Woolf, 2006). From a scienti¯c viewpoint it is agreed that consciousness is a function of the brain (Koch, 2004; Walker, 1970). The brain includes a collection of highly organized electrically excitable cells (neurons and glia) that control the central nervous system in higher animals. The current belief in neuroscience is that when a critical level of complexity is reached, interacting neurons form a conscious experience. This approach marks consciousness as a highly non-linear, emergent property arising from neuronal features of the brain that are fully compatible with the laws of classical physics (Koch, 2004; Walker, 1970; Koch, 2004; Scott, 1995). Classical physics envisions objects such as the brain, as an aggregate of logically independent, local, functional units (neurons and glia), which only interact with their direct neighbors forming larger systems. Yet the question remains, how do spatially distributed brain activities bind together to produce the unity of conscious perception? Known broadly as the binding problem, and more speci¯cally as the combination problem (Revonsuo & Newman, 1999), it seeks a description of how objects, their background, as well as abstract or emotional features are combined into a single coherent experience. The classical physics-based description explains this in terms of non-linear and deterministic chaotic behavior leading to non-computable results, stating that it is not easy to predict this property of consciousness. This interpretation leaves the combination problem largely unanswered. 2. The Meter of Consciousness At an empirical level of measurable observations consciousness itself has been related with neuronal synchrony (Plankar et al., 2013; Uhlhaas et al., 2009; Tononi & Koch, 2008; Crick & Koch, 1990). Neuronal synchrony (Fig. 1), the synchronized oscillations of large neuronal groups, correlates strongly with cognitive functions (perception, attention, decision-making, learning, memory, consciousness), while disruption in patterned synchrony is observed in various brain disorders (Uhlhaas & Singer, 2010, 2006; Hammond et al., 2007). Consciously perceived stimuli result in a transient global enhancement of synchronous gamma oscillations between occipital, KEEPING TIME: QUANTUM BEATING AS THE BASIS FOR NEURAL SYNCHRONY 295 Fig. 1. (Color online) Reliability of task-positive changes in gamma (32–64 Hz) band cortico–cortical coherence. Blue dots indicate anatomically prescribed nodes. Red lines indicate coherence was reliably greater during the task. The thickness of the line indicates the magnitude of the reliability. Node-pairs with ratios below the 99.9th percentile are not shown. Data are shown on a template brain for viewing perspective. This image and caption are a reproduction of the original found in the Open Access publication (Bardouille & Boe, 2012) and used under the PLoS Creative Commons Attribution license. parietal and frontal cortices across brain hemispheres, while no such pattern is detected when the stimulus is not perceived (Senkowski et al., 2008; Melloni et al., 2007). This experimentally and objectively observed, large-scale coherent synchronization elicits a cascading pattern of processes required for consciousness and perceptual binding including maintenance of working memory, anticipatory attention, as well as perceptual stabilization (Uhlhaas et al., 2009). These coherent neuronal oscillations are not merely a by-product of brain function, but rather have a speci¯c operational role in the coordination of neuronal communication and the regulation of synaptic plasticity (Fell & Axmacher, 2011; Singer, 2009; Fries, 2009; Fries et al., 2007; Jensen et al., 2007; Uhlhaas & Singer, 2006). Yet it remains unclear how these various cognitive functions emerge from synchronized neuronal ¯ring. Neural oscillations themselves appear to represent a reference timeframe for neuronal signaling (Axmacher et al., 2006) with the nervous system likely utilizing a context-speci¯c information coding strategy (Jermakowicz & Casagrande, 2007). Rapid signaling via electrical synapses, and postsynaptic potential inhibition are important electrophysiological properties responsible for establishing temporal gaps allowing for the generation of action potentials by excitatory neurons (Bartos et al., 2007; Cardin et al., 2009). However, what remains unknown is how neurons function to produce short, transient episodes of synchrony, while quickly alternating between coherent and incoherent states associated with cognition (Uhlhaas et al., 2009; Melloni et al., 296 T. J. A. CRADDOCK, A. PRIEL & J. A. TUSZYNSKI 2007). Furthermore, it remains uncertain how these states extend and function over real cortical networks spanning several spatial and temporal scales. One possible classical physics-based mechanism that may explain how the brain could achieve this is the stochastic background noise (Plankar et al., 2013). Neural circuit dynamics, the balancing of synaptic excitation and inhibition, naturally generate a stochastic background, commonly thought of as white noise (Barbieri & Brunel, 2008; Renart et al., 2007; Mattia & Del Giudice, 2004; Compte et al., 2003). This balance emerges from dynamic neural activity and is required to rapidly regulate neuronal sensitivity to synchronized synaptic inputs (Atallah & Scanziani, 2009; Haider & McCormick, 2009). Indeed rapid control of neuronal sensitivity via synaptic bombardment is a fundamental property of cortical dynamics (Haider & McCormick, 2009). It has been suggested that regulation of neuronal excitation via stochastic synaptic bombardment can cause elevated levels of neuronal depolarization resulting in a rapid neuron response in a multiplicative manner to a variety of inputs (Plankar et al., 2013). Neural oscillations are extremely responsive to phase perturbations and high-frequency oscillations (Wang et al., 2010), but require speci¯c phase relations for encoding and decoding of information, thus without organization in this bombardment, speci¯c information would be lost as synaptic noise. One key element in the rapid transitions of cortical activity across various spatiotemporal scales is the scale-invariant cascade of neural activation observed in the higher-vertebrate cortex (Van De Ville et al., 2010; Petermann et al., 2009; Stam & De Bruin, 2004). Considering this stochastic background activity as a scale-free dynamics maintaining itself close to criticality would involve a richer, deeper level of sub-neural information processing possessing a dynamic order underlying the complex spatiotemporal neuronal oscillation patterns. 3. Deeper Rhythms Within each neuron there is a highly structured matrix of electrically responsive protein ¯laments responsible for maintaining cell morphology and transporting intracellular vesicles thus playing a signi¯cant role in neuronal development, di®erentiation, synaptic generation and neuronal plasticity (Fig. 2). Membrane-bound receptors and ion channels, integral to neuronal signaling, communicate bi-directionally with this neuronal cytoskeletal matrix. This bi-directional interaction (feedforward and feed-back mechanisms) appears to be essential for higher cognitive function (Craddock et al., 2010). The cytoskeleton can serve as a downstream target of neurotransmitters through ionic, and metal signaling (Craddock et al., 2012a), or through post-translational modi¯cations mediated by signal transduction pathways (e.g., phosphorylation events triggered by CaMKII binding) (Craddock et al., 2012b; Janke & Kneussel, 2010; Hamero® et al., 2010) a®ecting its interconnections and overall structure (Woolf et al., 2009; Gardiner et al., 2011). Furthermore, experiments support that disruption of cytoskeletal integrity directly reduces the KEEPING TIME: QUANTUM BEATING AS THE BASIS FOR NEURAL SYNCHRONY 297 Fig. 2. (Color online) Schematic representations of the neuronal cytoskeleton. Black - Membrane, Green - MT, Red - Actin, Purple - MT-associated protein (MAP), Blue - Nucleus, Yellow - Dendritic Spine/Receptor. (a) MT lattice in neuron soma, axons and dendrites with dendritic spines. (b) MT sca®old in dendrite enters dendritic spine and connects with receptors via actin sca®old. (c) Static MT sca®old in axon becomes dynamic MT sca®old in growth cone connecting to ¯lopodia and lamellipodia via actin sca®old. This image and caption are a reproduction of the original found in Craddock et al. (2012). propagation of action potentials although the exact mechanism for this is unknown (Gardiner et al., 2011). Conversely, the cytoskeleton has been shown to exert immediate control over neural signal transmission. For example, the functioning of the GABAA receptor, a key target for the action of anesthetics, appears to rely on the microtubule (MT) cytoskeleton as destruction of the MT network has been shown to cause a 78% decrease in receptor currents (Meyer et al., 2000). Additionally, hypoxia-induced cytoskeletal reordering has been shown to cause suppression of fast sodium channels in brainstem respiratory neurons (Mironov & Richter, 2008), while drug induced modi¯cations of MTs altered the activity of calcium-dependent inactivation of calcium channels in isolated rat hippocampal neurons (Furukawa et al., 2003; Furukawa & Mattson, 1995; Johnson & Byerly, 1994, 1993). Additionally, alterations in cytoskeletal integrity consistently modulate the gating properties of voltage- and ligand-gated ion channels of the major ionic currents, Na þ , K þ and Cl , and Ca 2þ ) independent of ¯lament transport roles (Sun et al., 2008; Schubert & Akopian, 2004; Strege et al., 2003; Shcherbatko et al., 1999; Janmey, 1998). Cytoskeletal reorganization can result in altered intracellular transport leading to modi¯ed ion channel placement. Nonetheless, while this can account for slower neuromodulation it does not adequately explain the rapid dynamic changes required for functional connectivity. Electric signaling along actin and MT cytoskeletal ¯laments however can o®er 298 T. J. A. CRADDOCK, A. PRIEL & J. A. TUSZYNSKI a rapid means of intracellular communication. A su±ciently large body of experimental, computational and theoretical studies exists to indicate plausibility of both ionic and electronic conduction along protein ¯laments comprising the cytoskeleton and o®ering the possibility of parallel signal processing channels (Freedman et al., 2010; Chelminiak et al., 2009; Sataric et al., 2009; Dixon et al., 2008; Priel & Tuszynski, 2008; Priel et al., 2005; Tuszynski et al., 2004; Lin & Cantiello, 1993; Cantiello et al., 1991). Both MTs and actin ¯laments are highly charged protein polymers. Within the cytosol ions of opposite charge condense around these protein surfaces in an attempt to counter their exposed charge (Wong & Pollack, 2010). Application of a voltage gradient, such as from an action potential, can induce counter-ionic propagation along the ¯laments in a nonlinear, soliton-like ionic wave (Sataric et al., 2009; Priel & Tuszynski, 2008; Priel et al., 2005; Tuszynski et al., 2004; Lin & Cantiello, 1993), e®ectively creating intracellular biological electrical wires. Actin and MT ¯laments display semi-conductive properties that depend on the adsorbed counter-ions (Priel et al., 2005; Lin & Cantiello, 1993; Cantiello et al., 1991) with actin ¯laments shown to display extremely coordinated dynamics (Angelini et al., 2003, 2006). Recently, a concept for real-time neural computation of temporal processing has been proposed explaining the existence and function of so-called \microcircuits" in the brain (Kalisman et al., 2005). This model suggests that brain-wide neural assemblies, and microcircuits are not task-dependent, and that their dynamics change continuously without converging to a particular attractor state. This non-speci¯c, high-dimensional dynamical system, is e®ectively a \liquid state machine" (LSM) (Maass et al., 2002, 2003). The basic structure of a LSM is an excitable medium (i.e., a \liquid") with a continuous stream of input data being injected to the liquid module which then evolves its internal state to generate an output stream. Priel et al. (2006, 2010) previously suggested that the neuronal cytoskeleton in cytosol acts as such an LSM to form intracellular microcircuits in the neuron. The sequence of events suggested is outlined in Fig. 3. Electrical signals arrive at the postsynaptic density (PSD) as a consequence of traditional synaptic transmission, which in turn transmit ionic waves along actin ¯laments (Fig. 3(a)). This is followed by electrical signals propagating in the form of ionic waves through actin ¯laments to the MT matrix (Fig. 3(b)). Finally, the MT network operates as a high-dimensional state machine, evolving these input states by dynamically changing the °ow associated with individual MTs and/or by supporting nonlinear wave collisions (Fig. 3 (c)). The computed output from the MT matrix is the state of the system at any given time that is being transmitted by actin ¯laments to remote ion channels. This output function is presumably responsible for regulating the temporal gating state of voltage–sensitive channels (Fig. 3(d)). One particularly interesting case is when electrical signals transmitted along the cytoskeleton regulate the membrane potential at the axon hillock by changing the distribution and topology of open versus closed voltage–gated channels. This represents a unique opportunity for cytoskeletal signaling to regulate neuronal ¯ring. KEEPING TIME: QUANTUM BEATING AS THE BASIS FOR NEURAL SYNCHRONY 299 Fig. 3. Cut-away view of the dendritic shaft where MTs are interconnected by MT-associated protein 2 (MAP2). Connections between MTs and actin ¯laments are shown as well. Actin bundles bind to the post-synaptic density (PSD). On the upper left-hand side, a spiny synapse is shown where actin bundles enter the spine neck and bind to the PSD. Nonlinear wave propagation along MTs and actin ¯laments, interacts with and regulates neural membrane components such as ion channels, receptors for transmitters, adaptor proteins and sca®olding proteins. This image and caption are a reproduction of the ¯gure found in the open access publication (Priel et al., 2010) and used under the Springer Creative Commons Attribution Noncommercial License. As the neuronal cytoskeletal network e®ectively connects synapses throughout the cell, electric perturbation (e.g., calcium in°ux at the PSD, etc) would propagate throughout the network responding to multiple inputs. The resulting signal, composed and integrated from these multiple inputs, could then a®ect the neuron response through electrical control of voltage–gated ion channels (Priel et al., 2010; Craddock et al., 2010) a®ecting neural signaling and higher cognitive function. One such mechanism may be the temporal focusing of synaptic inputs, by coincidence detection, to allow for communication via synchrony (Fell & Axmacher, 2011; Fries, 2009). Another potential mechanism involves the interaction between cytoskeletal electric signaling and electromagnetic ¯elds. In this latter case condensed counter–ion clouds surrounding cytoskeletal ¯laments would e®ectively act as antennae to enhance, and amplify the neural response to exogenous or endogenous electromagnetic ¯elds (Funk et al., 2009; Gartzke & Lange, 2002). However, even these mechanisms would require some form of long–range coordination. 4. An Underlying Quantum Beat Classically, Brownian motion, the random motion of molecules in a liquid or gaseous medium, is believed to be truly stochastic ruling out long-range order in molecular biological systems. Nevertheless, as remarked by Erwin Schr€odinger several decades ago, classical physics alone may be insu±cient to explain the robust organization 300 T. J. A. CRADDOCK, A. PRIEL & J. A. TUSZYNSKI observed in living systems (Schr€ odinger, 1944). Herbert Fr€ohlich (Fr€ohlich, 1968, 1975, 1978) ¯rst proposed that quantum dipole oscillations within the hydrophobic interiors of proteins engage in long-range macroscopic coherence, regulating protein conformation and function. Since this proposal was ¯rst made, there has been a tremendous increase in experimental studies of biomolecular coherence. In recent years, without question, the most widely cited study experimentally demonstrating quantum e®ects in biology is Engel and colleagues direct observation of quantum beating due to electronic coherence in the Fenna–Matthews–Olsen (FMO) photosynthetic light harvesting complex (Engel et al., 2007). Initially this e®ect was observed at the relatively cold temperature of 77 K however, this limit has since been pushed to 277 K, nearing physiological temperature and e®ectively ruling out the warm and wet limit for quantum phenomena in biology (Panitchayangkoon et al., 2010). Furthermore, these quantum coherent e®ects do not seem to be restricted to the FMO complex alone, and have been shown to operate in the light harvesting complexes of plants (LHCII) (Schlau–Cohen et al., 2012; Calhoun et al., 2009; Schlau–Cohen et al., 2009), bacteria (LH2) (Ostroumov et al., 2013; Harel & Engel, 2012) and phycobiliproteins (Turner et al., 2012; Collini et al., 2010). It is hard to imagine that the use of quantum processes in plants and bacteria would not be continued through evolutionary achievements into higher-developed life forms such as mammals. Energy production mechanisms in plants involve light harvesting through chlorophyll while animals predominantly utilize glucose metabolism in mitochondria. It is therefore expected that at least some of the many complex steps involving oxidative phosphorylation in mitochondria, such as electron transfer in the mitochondrial protein complex I, employ quantum tunneling. In recent years the ¯eld of quantum biology has leapt from these demonstrations leading to proposals for quantum mechanisms of magnetoreception in birds, olfaction (Lambert et al., 2012), as well as individual photon e®ects in vision (Fleming et al., 2011). Thus, there is potential for quantum e®ects to occur within the unique biological environment of the neuronal cytoskeleton. It is our belief that there are more quantum mechanical processes playing an important role at the level of cell biology. Among naturally occurring amino acids, three possess °uorescent aromatic chromophores: tryptophan, tyrosine and phenylalanine. Tryptophan, tyrosine and phenylalanine possess resonant ring structures in which electrons are mobile and delocalizable and thus, due to their high polarizability, they are convenient sites for electronic energy transfer. Tryptophan is the most highly suited amino acid for transferring electrons and exchanging photons, as it has the greatest electron resonance and is thus the most °uorescent, however both tyrosine and phenylalanine may play a supporting role. Intramolecular singlet excitation energy transfer among and between tryptophan, tyrosine and phenylalanine has been shown to occur in a protein environment (Visser et al., 2008; Eisinger et al., 1969; Karreman et al., 1958). Fluorescent resonant energy transfer between aromatic residues and other °uorophores is a technique commonly used to probe protein structure and the conformational changes required for proper function. In most cases KEEPING TIME: QUANTUM BEATING AS THE BASIS FOR NEURAL SYNCHRONY 301 this resonant energy transfer is restricted to a single isolated protein, or between two adjacent interacting proteins or molecules. Globular proteins stabilized in crystal form can e±ciently transfer energy between chromophoric residues (Desie et al., 1986), yet these structures are arti¯cial constructs and are therefore not expected to be biologically relevant. However, protein polymers, such as the cell cytoskeleton, are pervasive in biology, providing ideal structures for this type of energy transmission. In the highly structured neuron, various MAPs interconnect MTs into networks, forming the sca®olding for the neuronal and synaptic architecture. In axons, MTs form long continuous structures orienting with the same polarity, while in dendrites they form as short interrupted ¯laments of mixed polarity. These structures in neurons are relatively stable, as opposed to the dynamic instability observed in all other cell types. The MT constituent protein tubulin possesses a unique network of chromophoric amino acid residues (Fig. 4), similar to the chlorophyll architectures observed in photosynthetic light harvesting complexes. These aromatic chromophores could support coherent quantum oscillations within MTs and allow for the emergence of quantum states in protein ¯laments of the cytoskeleton. The stability, length and oriented polarity of these networks are expected to play a role in both ionic and electronic signal conduction. Such rapid signaling through aromatic conduction pathways may coordinate the complex organization of the MT cytoskeleton required for the tasks of cell division, motor protein tra±cking and motility. (a) (b) (c) (d) Fig. 4. (Color online) Unique network of chromophoric amino acid in MTs. Light grey alpha tubulin; dark grey beta tubulin; blue tryptophan residues; purple tyrosine residues; green phenylalanine residues. (a) MT fragment. (b) MT constituent protein dimer tubulin. (c) A patch of MT showing a nine tubulin dimer lattice. (D) End-view of MT showing MT lumen. Scale bar approximately 5 nm. 302 T. J. A. CRADDOCK, A. PRIEL & J. A. TUSZYNSKI Arrays of aromatics, behaving as cellular automata, have been shown to be capable of solving a variety of computationally intense problems in a manner that could potentially far exceed the capabilities of todays computers (Adamatzky, 2010; Bandyopadhyay et al., 2010). Cellular automata models of MTs have shown that their geometry is conducive to such computations (Craddock et al., 2009; Rasmussen et al., 1990; Hamero® et al., 1986), which may underlie the coordination of MT architecture and intracellular transport required for proper neuron development and function. While aromatic excitation dynamics in MTs have not speci¯cally been investigated, there is a high likelihood that they would be able to support this form of computation. Supportive of this notion, MTs have been shown to reorganize in a dose-dependent manner after exposure to UV light (Krasylenko et al., 2013; Staxen et al., 1993; Zamansky & Chou, 1987; Zaremba et al., 1984). Feasible mechanisms for these changes include the reduction of disul¯de or peptide bonds induced by photoexcitation of tryptophan groups (Wu et al., 2008; Neves–Petersen et al., 2002; Vanhooren et al., 2002; Weisenborn et al., 1996), or subtle protein structural changes due to photo-induced alterations in tryptophan °exibility (Weisenborn et al., 1996). Such a signaling mechanism may explain the observations of an apparent UV mediated cell-to-cell in°uence on cell division (Fels, 2009). At the cellular level living systems emit ultra-weak spontaneous photons without external excitation (Kobayashi et al., 2009; Chang, 2008; Van Wijk et al., 2006; Yoon et al., 2005; Takeda et al., 2004; Kobayashi & Inaba, 2000; Cohen & Popp, 1997; Devaraj et al., 1991; Quickenden & Que Hee, 1974). These photons are produced via various biochemical reactions, but principally from bioluminescent radical reactions of reactive oxygen and nitrogen species and the relaxation of excited states. The oxidative metabolism of mitochondria and lipid peroxidation appear to be a primary source for this activity (Nakano, 2005; Thar & Kuhl, 2004). Neurons also continuously produce photons during their ordinary metabolism (Kataoka et al., 2001; Isojima et al., 1995), and it has been shown in vivo that the intensity of photon emission from rat brain correlates with cerebral energy metabolism, electrical activity, blood °ow and oxidative stress (Kobayashi et al., 1999a,b). Furthermore, Sun et al. (2010) have revealed that ultraweak bioluminescent photons can conduct along neural ¯bers and can be considered as a means of neural communication. Radical recombination within mitochondria can emit photons in the UV range required to excite the chromophoric network within MTs (Voeikov, 2001). Thus it is suggested that biophoton emission and bioelectronic activities are not independent of biological events in the nervous system, and their synergistic action may play an important role in cytoskeletal ionic signaling, neural signal transduction and further to neural synchrony. Only further investigation, both theoretically and experimentally, will tell. 5. Dropping the Beat Based on our knowledge of both structural biology and drug binding properties of several classes of ligands, it is possible to extend the above line of thinking further. KEEPING TIME: QUANTUM BEATING AS THE BASIS FOR NEURAL SYNCHRONY 303 Tubulin has been thoroughly analyzed in recent years regarding its binding sites for various compounds, namely: (a) pharmacological agents used in chemotherapy (paclitaxel, vinca alkaloids, colchicine and others) (Jordan & Wilson, 2004), (b) anesthetics (Craddock et al., 2012), (c) psychoactive compounds (e.g., noscapine (Alisaraie & Tuszynski, 2011)). It is instructive to analyze the location and strength of binding for these compounds. The chemotherapeutic agents bind in various locations depending on the e®ect, i.e., paclitaxel in the luminal location of MTs to enhance their stability, vinca alkaloids in the beta tubulin to alpha tubulin interdimer binding location, which caps MTs and prevents their further growth, colchicine binds at the beta–alpha intradimer interface causing a conformational change of tubulin and making it assembly incompetent. Anesthetics, drugs that act to erase conscious experience, have been found to bind to numerous locations on the tubulin surface with relatively low a±nity, including some locations that destabilize the MT lattice (Craddock et al., 2012c). Futhermore, these predicted binding locations are conveniently placed to block exciton transfer between tryptophans (Fig. 5). Evidence shows that anesthetics retard electron mobility such that the movement of free electrons in a corona discharge is inhibited by anesthetics (Hamero® & Watt, 1983). By forming their own attractions in hydrophobic pockets via van der Waals forces or hydrogen bonding, anesthetics may inhibit electronic energy transfer required for protein dynamics, disrupting molecular coherence, and subsequently neural synchrony. On the other hand, psychoactive drugs such as the opioid noscapine, and hallucinogenic psychedelics including tryptamines, such as DMT, ergolines, such as LSD and phenylethylamines, such as MDMA, are based on cyclical aromatic structures (benzene and indole rings), exactly like those found in the aromatic amino acids tryptophan, tyrosine and phenylalanine. Additional chromophoric sites, strategically located along the MT length could enhance electronic energy transfer. Supportive of this are Fig. 5. Unique network of chromophoric amino acid in MTs. Light grey alpha tubulin; dark grey beta tubulin; blue tryptophan residues; purple tyrosine residues; green phenylalanine residues. (a) MT fragment. (b) MT constituent protein dimer Tubulin. (c) A patch of MT showing nine tubulin dimer lattice. (d) End-view of MT showing MT lumen. 304 T. J. A. CRADDOCK, A. PRIEL & J. A. TUSZYNSKI studies showing that a drug's psychedelic potency correlates with electron resonance donation (Nichols et al., 1977; Kang & Green, 1970; Snyder & Merrill, 1965). Taken together, the dependence of protein conformational regulation on photoinduced modulation of aromatic residue °exibility, these anesthetic and psychedelic studies suggest that (1) consciousness depends on quantum coherent oscillations and (2) that these quantum processes are inhibited/promoted by anesthetics/psychedelics which impair/enchance resonant energy transfer in cytoskeletal proteins. 6. Summary In this paper we have discussed the hypothesis that quantum coherent oscillations may be playing a role in neuronal signaling and outline a molecular basis for this possibility. In view of recent experimental evidence of quantum beats in LHCII and bacteria, it is logical to seek similar e®ects in important structures found in animal cells, especially in neurons. After all, it is common in nature to preserve evolutionary advances. If bacteria and plants found a way to harness electromagnetic energy using quantum processes, why would not animals ¯nd a use for this method of energy and information transmission? We argue that MTs, which play critical roles in all eukaryotic cells, possess structural and functional characteristics that are consistent with quantum coherent excitations in the aromatic groups of their tryptophan residues. We further outline the consequences of these ¯ndings on neuronal processes including the emergence of consciousness. 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