Do mental events cause neural events analogously to the probability fields of quantum mechanics?

If non-material mental events, such as the intention to carry out an action, are to have an effective action on neural events in the brain, it has to be at the most subtle and plastic level of these events. In the first stage of our enquiry an introduction to conventional synaptic theory leads on to an account of the manner of operation of the ultimate synaptic units. These units are the synaptic boutons that, when excited by an all-or-nothing nerve impulse, deliver the total contents of a single synaptic vesicle, not regularly, but probabilistically. This quantal emission of the synaptic transmitter molecules (about 5000-10 000) is the elementary unit of the transmission process from one neuron to another. In the second stage this refined physiological analysis leads on to an account of the ultrastructure of the synapse, which gives clues as to the manner of its unitary probabilistic operation. The essential feature is that the effective structure of each bouton is a paracrystalline presynaptic vesicular grid with about 50 vesicles, which acts probabilistically in vesicular (quantal) release. In the third stage it is considered how a non-material mental event, such as an intention to move, could influence the subtle probabilistic operations of synaptic boutons. On the biological side, attention is focused on the paracrystalline presynaptic vesicular grids as the targets for non-material mental events. On the physical side, attention is focused on the probabilistic fields of quantum mechanics which carry neither mass nor energy, but which nevertheless can exert effective action at microsites. The new light on the mind-brain problem came from the hypothesis that the non-material mental events, the 'World 2' of Popper, relate to the neural events of the brain (the 'World 1' of matter and energy) by actions in conformity with quantum theory. This hypothesis that mental events act on probabilistic synaptic events in a manner analogous to the probability fields of quantum mechanics seems to open up an immense field of scientific investigation both in quantum physics and in neuroscience.     

Computational and experimental studies on the catalytic mechanism of biliverdin-IXbeta reductase

BVR-B (biliverdin-IXbeta reductase) also known as FR (flavin reductase) is a promiscuous enzyme catalysing the pyridine-nucleotide-dependent reduction of a variety of flavins, biliverdins, PQQ (pyrroloquinoline quinone) and ferric ion. Mechanistically it is a good model for BVR-A (biliverdin-IXalpha reductase), a potential pharmacological target for neonatal jaundice and also a potential target for adjunct therapy to maintain protective levels of biliverdin-IXalpha during organ transplantation. In a commentary on the structure of BVR-B it was noted that one outstanding issue remained: whether the mechanism was a concerted hydride transfer followed by protonation of a pyrrolic anion or protonation of the pyrrole followed by hydride transfer. In the present study we have attempted to address this question using QM/MM (quantum mechanics/molecular mechanics) calculations. QM/MM potential energy surfaces show that the lowest energy pathway proceeds with a positively charged pyrrole intermediate via two transition states. These initial calculations were performed with His(153) as the source of the proton. However site-directed mutagenesis studies with both the H153A and the H153N mutant reveal that His(153) is not required for catalytic activity. We have repeated the calculation with a solvent hydroxonium donor and obtain a similar energy landscape indicating that protonation of the pyrrole is the most likely first step followed by hydride transfer and that the required proton may come from bulk solvent. The implications of the present study for the design of inhibitors of BVR-A are discussed.     

Top-Down Modulation on Perceptual Decision with Balanced Inhibition through Feedforward and Feedback Inhibitory Neurons

Recent physiological studies have shown that neurons in various regions of the central nervous systems continuously receive noisy excitatory and inhibitory synaptic inputs in a balanced and covaried fashion. While this balanced synaptic input (BSI) is typically described in terms of maintaining the stability of neural circuits, a number of experimental and theoretical studies have suggested that BSI plays a proactive role in brain functions such as top-down modulation for executive control. Two issues have remained unclear in this picture. First, given the noisy nature of neuronal activities in neural circuits, how do the modulatory effects change if the top-down control implements BSI with different ratios between inhibition and excitation? Second, how is a top-down BSI realized via only excitatory long-range projections in the neocortex? To address the first issue, we systematically tested how the inhibition/excitation ratio affects the accuracy and reaction times of a spiking neural circuit model of perceptual decision. We defined an energy function to characterize the network dynamics, and found that different ratios modulate the energy function of the circuit differently and form two distinct functional modes. To address the second issue, we tested BSI with long-distance projection to inhibitory neurons that are either feedforward or feedback, depending on whether these inhibitory neurons do or do not receive inputs from local excitatory cells, respectively. We found that BSI occurs in both cases. Furthermore, when relying on feedback inhibitory neurons, through the recurrent interactions inside the circuit, BSI dynamically and automatically speeds up the decision by gradually reducing its inhibitory component in the course of a trial when a decision process takes too long.     

On the Influence of Observation of the Processes in Quantum Systems: Is it Possible to Determine an Observer Effect in Biological Systems?

Biophysics - Abstract—The issue of how observation of a process in quantum mechanics may influence its outcome is described by case studies of quantum emission by a two-level system and the...     

tRNA structure from a graph and quantum theoretical perspective

One of the objectives of theoretical biochemistry is to find a suitable representation of molecules allowing us to encode what we know about their structures, interactions and reactivity. Particularly, tRNA structure is involved in some processes like aminoacylation and genetic code translation, and for this reason these molecules represent a biochemical object of the utmost importance requiring characterization. We propose here two fundamental aspects for characterizing and modeling them. The first takes into consideration the connectivity patterns, i.e. the set of linkages between atoms or molecular fragments (a key tool for this purpose is the use of graph theory), and the second one requires the knowledge of some properties related to the interactions taking place within the molecule, at least in an approximate way, and perhaps of its reactivity in certain means. We used quantum mechanics to achieve this goal; specifically, we have used partial charges as a manifestation of the reply to structural changes. These charges were appropriately modified to be used as weighted factors for elements constituting the molecular graph. This new graph-tRNA context allow us to detect some structure-function relationships.     

Connexin channel permeability to cytoplasmic molecules

Connexin channels are known to be permeable to a variety of cytoplasmic molecules. The first observation of second messenger junctional permeability, made approximately 30 years ago, sparked broad interest in gap junction channels as mediators of intercellular molecular signaling. Since then, much has been learned about the diversity of connexin channels with regard to isoform diversity, tissue and developmental distribution, modes of channel regulation, assembly, expression, biochemical modification and permeability, all of which appear to be dynamically regulated. This information has expanded the potential roles of connexin channels in development, physiology and disease, and made their elucidation much more complex--30 years ago such an orchestra of junctional dynamics was unanticipated. Only recently, however, have investigators been able to directly address, in this more complex framework, the key issue: what specific biological molecules, second messengers and others, are able to permeate the various types of connexin channels, and how well? An important related issue, given the ever-growing list of connexin-related pathologies, is how these permeabilities are altered by disease-causing connexin mutations. Together, many studies show that a variety of cytoplasmic molecules can permeate the different types of connexin channels. A few studies reveal differences in permeation by different molecules through a particular type of connexin channel, and differences in permeation by a particular molecule through different types of connexin channels. This article describes and evaluates the various methods used to obtain these data, presents an annotated compilation of the results, and discusses the findings in the context of what can be inferred about mechanism of selectivity and potential relevance to signaling. The data strongly suggest that highly specific interactions take place between connexin pores and specific biological molecular permeants, and that those interactions determine which cytoplasmic molecules can permeate and how well. At this time, the nature of those interactions is unclear. One hopes that with more detailed permeability and structural information, the specific molecular mechanisms of the selectivity can be elucidated.     

Noise-induced modulation of the relaxation kinetics around a non-equilibrium steady state of non-linear chemical reaction networks

Stochastic effects from correlated noise non-trivially modulate the kinetics of non-linear chemical reaction networks. This is especially important in systems where reactions are confined to small volumes and reactants are delivered in bursts. We characterise how the two noise sources confinement and burst modulate the relaxation kinetics of a non-linear reaction network around a non-equilibrium steady state. We find that the lifetimes of species change with burst input and confinement. Confinement increases the lifetimes of all species that are involved in any non-linear reaction as a reactant. Burst monotonically increases or decreases lifetimes. Competition between burst-induced and confinement-induced modulation may hence lead to a non-monotonic modulation. We quantify lifetime as the integral of the time autocorrelation function (ACF) of concentration fluctuations around a non-equilibrium steady state of the reaction network. Furthermore, we look at the first and second derivatives of the ACF, each of which is affected in opposite ways by burst and confinement. This allows discriminating between these two noise sources. We analytically derive the ACF from the linear Fokker-Planck approximation of the chemical master equation in order to establish a baseline for the burst-induced modulation at low confinement. Effects of higher confinement are then studied using a partial-propensity stochastic simulation algorithm. The results presented here may help understand the mechanisms that deviate stochastic kinetics from its deterministic counterpart. In addition, they may be instrumental when using fluorescence-lifetime imaging microscopy (FLIM) or fluorescence-correlation spectroscopy (FCS) to measure confinement and burst in systems with known reaction rates, or, alternatively, to correct for the effects of confinement and burst when experimentally measuring reaction rates.     

Functional interactions in bacteriorhodopsin: a theoretical analysis of retinal hydrogen bonding with water.

The light-driven proton pump, bacteriorhodopsin (bR) contains a retinal molecule with a Schiff base moiety that can participate in hydrogen-bonding interactions in an internal, water-containing channel. Here we combine quantum chemistry and molecular mechanics techniques to determine the geometries and energetics of retinal Schiff base-water interactions. Ab initio molecular orbital calculations are used to determine potential surfaces for water-Schiff base hydrogen-bonding and to characterize the energetics of rotation of the C-C single bond distal and adjacent to the Schiff base NH group. The ab initio results are combined with semiempirical quantum chemistry calculations to produce a data set used for the parameterization of a molecular mechanics energy function for retinal. Using the molecular mechanics force field the hydrated retinal and associated bR protein environment are energy-minimized and the resulting geometries examined. Two distinct sites are found in which water molecules can have hydrogen-bonding interactions with the Schiff base: one near the NH group of the Schiff base in a polar region directed towards the extracellular side, and the other near a retinal CH group in a relatively nonpolar region, directed towards the cytoplasmic side.     

Effect of Landscape Structure on Species Diversity

The effects of habitat fragmentation and their implications for biodiversity is a central issue in conservation biology which still lacks an overall comprehension. There is not yet a clear consensus on how to quantify fragmentation even though it is quite common to couple the effects of habitat loss with habitat fragmentation on biodiversity. Here we address the spatial patterns of species distribution in fragmented landscapes, assuming a neutral community model. To build up the fragmented landscapes, we employ the fractional Brownian motion approach, which in turn permits us to tune the amount of habitat loss and degree of clumping of the landscape independently. The coupling between the neutral community model, here simulated by means of the coalescent method, and fractal neutral landscape models enables us to address how the species–area relationship changes as the spatial patterns of a landscape is varied. The species–area relationship is one of the most fundamental laws in ecology, considered as a central tool in conservation biology, and is used to predict species loss following habitat disturbances. Our simulation results indicate that the level of clumping has a major role in shaping the species–area relationship. For instance, more compact landscapes are more sensitive to the effects of habitat loss and speciation rate. Besides, the level of clumping determines the existence and extension of the power-law regime which is expected to hold at intermediate scales. The distributions of species abundance are strongly influenced by the degree of fragmentation. We also show that the first and second commonest species have approximately self-similar spatial distributions across scales, with the fractal dimensions of the support of the first and second commonest species being very robust to changes in the spatial patterns of the landscape.     

Computational alanine scanning with linear scaling semiempirical quantum mechanical methods

Alanine scanning is a powerful experimental tool for understanding the key interactions in protein–protein interfaces. Linear scaling semiempirical quantum mechanical calculations are now sufficiently fast and robust to allow meaningful calculations on large systems such as proteins, RNA and DNA. In particular, they have proven useful in understanding protein–ligand interactions. Here we ask the question: can these linear scaling quantum mechanical methods developed for protein–ligand scoring be useful for computational alanine scanning? To answer this question, we assembled 15 protein–protein complexes with available crystal structures and sufficient alanine scanning data. In all, the data set contains ΔΔGs for 400 single point alanine mutations of these 15 complexes. We show that with only one adjusted parameter the quantum mechanics‐based methods outperform both buried accessible surface area and a potential of mean force and compare favorably to a variety of published empirical methods. Finally, we closely examined the outliers in the data set and discuss some of the challenges that arise from this examination. Proteins 2010. © 2010 Wiley‐Liss, Inc.     

Domain interactions within Fzo1 oligomers are essential for mitochondrial fusion

Mitofusins are conserved GTPases essential for the fusion of mitochondria. These mitochondrial outer membrane proteins contain a GTPase domain and two or three regions with hydrophobic heptad repeats, but little is known about how these domains interact to mediate mitochondrial fusion. To address this issue, we have analyzed the yeast mitofusin Fzo1p and find that mutation of any of the three heptad repeat regions (HRN, HR1, and HR2) leads to a null allele. Specific pairs of null alleles show robust complementation, indicating that functional domains need not exist on the same molecule. Biochemical analysis indicates that this complementation is due to Fzo1p oligomerization mediated by multiple domain interactions. Moreover, we find that two non-overlapping protein fragments, one consisting of HRN/GTPase and the other consisting of HR1/HR2, can form a complex that reconstitutes Fzo1p fusion activity. Each of the null alleles disrupts the interaction of these two fragments, suggesting that we have identified a key interaction involving the GTPase domain and heptad repeats essential for fusion.     

Potential for total nitrogen removal by combining vertical flow and horizontal flow constructed wetlands: A full-scale experiment study

To improve total nitrogen removal, a full-scale experimental study was conducted on a hybrid constructed wetlands plant designed for 100 person equivalents. The plant was composed of a first stage of vertical filters (fed with raw wastewater), followed by a second stage of horizontal filters. It was monitored over one year, measuring hydraulic conditions, physico-chemical conditions, gas emission, oxygen levels in the gas phase as well as regular treatment performance by 24-h composite samples. Different vertical filter configurations (media depth, intermediate and passive aeration system) were tested as well as two horizontal filter designs. Nitrogen removal is discussed in terms of the efficiency of each stage in relation to the season and the load applied. This study indicates limits for systems configuration and suggests some design avenues for hybrid systems to reach high and regular levels of nitrogen removal with reasonable surface area per person.     

Review. Theoretical and empirical evidence for the impact of inductive biases on cultural evolution

The question of how much the outcomes of cultural evolution are shaped by the cognitive capacities of human learners has been explored in several disciplines, including psychology, anthropology and linguistics. We address this question through a detailed investigation of transmission chains, in which each person passes information to another along a chain. We review mathematical and empirical evidence that shows that under general conditions, and across experimental paradigms, the information passed along transmission chains will be affected by the inductive biases of the people involved-the constraints on learning and memory, which influence conclusions from limited data. The mathematical analysis considers the case where each person is a rational Bayesian agent. The empirical work consists of behavioural experiments in which human participants are shown to operate in the manner predicted by the Bayesian framework. Specifically, in situations in which each person's response is used to determine the data seen by the next person, people converge on concepts consistent with their inductive biases irrespective of the information seen by the first member of the chain. We then relate the Bayesian analysis of transmission chains to models of biological evolution, clarifying how chains of individuals correspond to population-level models and how selective forces can be incorporated into our models. Taken together, these results indicate how laboratory studies of transmission chains can provide information about the dynamics of cultural evolution and illustrate that inductive biases can have a significant impact on these dynamics.