Perceptual learning with perceptions

In this work we present an approach to understand neuronal mechanisms underlying perceptual learning. Experimental results achieved with stimulus patterns of coherently moving dots are considered to build a simple neuronal model. The design of the model is made transparent and underlying behavioral assumptions made explicit. The key aspect of the suggested neuronal model is the learning algorithm used: We evaluated an implementation of Hebbian learning and are thus able to provide a straight-forward model capable to explain the neuronal dynamics underlying perceptual learning. Moreover, the simulation results suggest a very simple explanation for the aspect of “sub-threshold” learning (Watanabe et al. in Nature 413:844–884, 2001) as well as the relearning of motion discrimination after damage to primary visual cortex as recently reported (Huxlin et al. in J Neurosci 29:3981–3991, 2009) and at least indicate that perceptual learning might only occur when accompanied by conscious percepts.     

Dynamic formation of oriented patches in chondrocyte cell cultures

Growth factors have a significant impact not only on the growth dynamics but also on the phenotype of chondrocytes (Barbero et al. in J. Cell. Phys. 204:830–838, 2005). In particular, as chondrocytes approach confluence, the cells tend to align and form coherent patches. Starting from a mathematical model for fibroblast populations at equilibrium (Mogilner et al. in Physica D 89:346–367, 1996), a dynamic continuum model with logistic growth is developed. Both linear stability analysis and numerical solutions of the time-dependent nonlinear integro-partial differential equation are used to identify the key parameters that lead to pattern formation in the model. The numerical results are compared quantitatively to experimental data by extracting statistical information on orientation, density and patch size through Gabor filters.     

Response probability and response time: a straight line, the Tagging/Retagging interpretation of short term memory, an operational definition of meaningfulness and short term memory time decay and search time

The functional relationship between correct response probability and response time is investigated in data sets from Rubin, Hinton and Wenzel, J Exp Psychol Learn Mem Cogn 25:1161–1176, 1999 and Anderson, J Exp Psychol [Hum Learn] 7:326–343, 1981. The two measures are linearly related through stimulus presentation lags from 0 to 594 s in the former experiment and for repeated learning of words in the latter. The Tagging/Retagging interpretation of short term memory is introduced to explain this linear relationship. At stimulus presentation the words are tagged. This tagging level drops slowly with time. When a probe word is reintroduced the tagging level has to increase for the word to be properly identified leading to a delay in response time. The tagging time is related to the meaningfulness of the words used—the more meaningful the word the longer the tagging time. After stimulus presentation the tagging level drops in a logarithmic fashion to 50% after 10 s and to 20% after 240 s. The incorrect recall and recognition times saturate in the Rubin et al. data set (they are not linear for large time lags), suggesting a limited time to search the short term memory structure: the search time for recall of unusual words is 1.7 s. For recognition of nonsense words the corresponding time is about 0.4 s, similar to the 0.243 s found in Cavanagh (1972).     

A Computational Analysis of Localized Ca<Superscript>2+</Superscript>-Dynamics Generated by Heterogeneous Release Sites

We investigate the role of heterogeneous expression of IP₃R and RyR in generating diverse elementary Ca²⁺ signals. It has been shown empirically (Wojcikiewicz and Luo in Mol. Pharmacol. 53(4):656–662, 1998; Newton et al. in J. Biol. Chem. 269(46):28613–28619, 1994; Smedt et al. in Biochem. J. 322(Pt. 2):575–583, 1997) that tissues express various proportions of IP₃ and RyR isoforms and this expression is dynamically regulated (Parrington et al. in Dev. Biol. 203(2):451–461, 1998; Fissore et al. in Biol. Reprod. 60(1):49–57, 1999; Tovey et al. in J. Cell Sci. 114(Pt. 22):3979–3989, 2001). Although many previous theoretical studies have investigated the dynamics of localized calcium release sites (Swillens et al. in Proc. Natl. Acad. Sci. U.S.A. 96(24):13750–13755, 1999; Shuai and Jung in Proc. Natl. Acad. Sci. U.S.A. 100(2):506–510, 2003a; Shuai and Jung in Phys. Rev. E, Stat. Nonlinear Soft Matter Phys. 67(3 Pt. 1):031905, 2003b; Thul and Falcke in Biophys. J. 86(5):2660–2673, 2004; DeRemigio and Smith in Cell Calcium 38(2):73–86, 2005; Nguyen et al. in Bull. Math. Biol. 67(3):393–432, 2005), so far all such studies focused on release sites consisting of identical channel types. We have extended an existing mathematical model (Nguyen et al. in Bull. Math. Biol. 67(3):393–432, 2005) to release sites with two (or more) receptor types, each with its distinct channel kinetics. Mathematically, the release site is represented by a transition probability matrix for a collection of nonidentical stochastically gating channels coupled through a shared Ca²⁺ domain. We demonstrate that under certain conditions a previously defined mean-field approximation of the coupling strength does not accurately reproduce the release site dynamics. We develop a novel approximation and establish that its performance in these instances is superior. We use this mathematical framework to study the effect of heterogeneity in the Ca²⁺-regulation of two colocalized channel types on the release site dynamics. We consider release sites consisting of channels with both Ca²⁺-activation and inactivation (“four-state channels”) and channels with Ca²⁺-activation only (“two-state channels”) and show that for the appropriate parameter values, synchronous channel openings within a release site with any proportion of two-state to four-state channels are possible, however, the larger the proportion of two-state channels, the more sensitive the dynamics are to the exact spatial positioning of the channels and the distance between channels. Specifically, the clustering of even a small number of two-state channels interferes with puff/spark termination and increases puff durations or leads to a tonic response.     

A PDE Model for Imatinib-Treated Chronic Myelogenous Leukemia

We derive a model for describing the dynamics of imatinib-treated chronic myelogenous leukemia (CML). This model is a continuous extension of the agent-based CML model of Roeder et al. (Nat. Med. 12(10), 1181–1184, 2006) and of its recent formulation as a system of difference equations (Kim et al. in Bull. Math. Biol. 70(3), 728–744, 2008). The new model is formulated as a system of partial differential equations that describe various stages of differentiation and maturation of normal hematopoietic cells and of leukemic cells. An imatinib treatment is also incorporated into the model. The simulations of the new PDE model are shown to qualitatively agree with the results that were obtained with the discrete-time (difference equation and agent-based) models. At the same time, for a quantitative agreement, it is necessary to adjust the values of certain parameters, such as the rates of imatinib-induced inhibition and degradation.     

Traveling EEG slow oscillation along the dorsal attention network initiates spontaneous perceptual switching

An ambiguous figure such as the Necker cube causes spontaneous perceptual switching (SPS). The mechanism of SPS in multistable perception has not yet been determined. Although early psychological studies suggested that SPS may be caused by fatigue or satiation of orientation, the neural mechanism of SPS is still unknown. Functional magnetic resonance imaging (fMRI) has shown that the dorsal attention network (DAN), which mainly controls voluntary attention, is involved in bistable perception of the Necker cube. To determine whether neural dynamics along the DAN cause SPS, we performed simultaneous electroencephalography (EEG) and fMRI during an SPS task with the Necker cube, with every SPS reported by pressing a button. This EEG–fMRI integrated analysis showed that (a) 3–4 Hz spectral EEG power modulation at fronto-central, parietal, and centro-parietal electrode sites sequentially appeared from 750 to 350 ms prior to the button press; and (b) activations correlating with the EEG modulation traveled along the DAN from the frontal to the parietal regions. These findings suggest that slow oscillation initiates SPS through global dynamics along the attentional system such as the DAN.     

Daphnia revisited: local stability and bifurcation theory for physiologically structured population models explained by way of an example

We consider the interaction between a general size-structured consumer population and an unstructured resource. We show that stability properties and bifurcation phenomena can be understood in terms of solutions of a system of two delay equations (a renewal equation for the consumer population birth rate coupled to a delay differential equation for the resource concentration). As many results for such systems are available (Diekmann et al. in SIAM J Math Anal 39:1023–1069, 2007), we can draw rigorous conclusions concerning dynamical behaviour from an analysis of a characteristic equation. We derive the characteristic equation for a fairly general class of population models, including those based on the Kooijman–Metz Daphnia model (Kooijman and Metz in Ecotox Env Saf 8:254–274, 1984; de Roos et al. in J Math Biol 28:609–643, 1990) and a model introduced by Gurney–Nisbet (Theor Popul Biol 28:150–180, 1985) and Jones et al. (J Math Anal Appl 135:354–368, 1988), and next obtain various ecological insights by analytical or numerical studies of special cases.     

A Model for Multi-site Pacing of Fibrillation Using Nonlinear Dynamics Feedback

Traditionally, cardiac defibrillation requires a strong electric shock. Many unwanted side effects of this shock could be eliminated if defibrillation were performed using weak stimuli applied to several locations throughout the heart. Such multi-site pacing algorithms have been shown to defibrillate both experimentally (Pak et al., Am J Physiol 285:H2704–H2711, 2003) and theoretically (Puwal and Roth, J Biol Systems 14:101–112, 2006). Gauthier et al. (Chaos, 12:952–961, 2002) proposed a method to pace the heart using an algorithm based on nonlinear dynamics feedback applied through a single electrode. Our study applies a related but simpler algorithm, which essentially configures each electrode as a demand pacemaker, to simulate the multi-site pacing of fibrillating cardiac tissue. We use the numerical model developed by Fenton et al. (Chaos, 12:852–892, 2002) as the reaction term in a reaction–diffusion equation that we solve over a two-dimensional sheet of tissue. The defibrillation rate after pacing for 3 s is about 30%, which is significantly higher than the spontaneous defibrillation rate and is higher than observed in previous experimental and theoretical studies. Tuning the algorithm period can increase this rate to 45%. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Visual perception of ambiguous figures: synchronization based neural models

We develop and study two neural network models of perceptual alternations. Both models have a star-like architecture of connections with a central element connected to a set of peripheral elements. A particular perception is simulated in terms of partial synchronization between the central element and some sub-group of peripheral elements. The first model is constructed from phase oscillators and the mechanism of perceptual alternations is based on chaotic intermittency under fixed parameter values. Similar to experimental evidence, the distribution of times between perceptual alternations is represented by the gamma distribution. The second model is built of spiking neurons of the Hodgkin–Huxley type. The mechanism of perceptual alternations is based on plasticity of inhibitory synapses which increases the inhibition from the central unit to the neural assembly representing the current percept. As a result another perception is formed. Simulations show that the second model is in good agreement with behavioural data on switching times between percepts of ambiguous figures and with experimental results on binocular rivalry of two and four percepts. This article is part of a special issue on Neuronal Dynamics of Sensory Coding. This special issue is in honour of Professor Pepe Segundo who is one of the pioneers in the study of neural coding. Pepe has been an active participant in many Neural Coding Workshops sharing his great knowledge and experience of research in this field. I (R. Borisyuk) was very happy to meet Pepe for the first time in Prague when attending the first Neural Coding Workshop in 1995. From that time we regularly met at Neural Coding Workshops and these meetings have always been very stimulating and fruitful for my research. Remarkably, the first paper I studied at the beginning of my scientific career was a seminal paper by Moore et al. (1970). For me, this paper provided a great opportunity to learn the basic statistical techniques for the analysis of multiple spike trains and neural coding. According to the Institute of Scientific Information, this paper has been cited 380 times! This exciting paper has inspired my research into the synaptic and functional connectivity of neural circuits derived from spike-train recordings (Borisyuk et al. 1985; Stuart et al. 2005) and guided my search for new ideas on neural coding.     

The role of topography in promoting fractal patchiness in a carbonate shelf landscape

Satellite remote sensing has shown numerous aspects of coral reef seascapes to be fractal. That is, they display characteristics of scale-invariance and complexity. To date, an understanding of why reefscapes adopt this curious scaling has been lacking. This property was investigated using high-resolution terrain models built using bathymetric LiDAR soundings of the shallow Puerto Rico insular shelf. A computer-simulation model constructed using simple random processes was adequate to describe many of the intricacies of actual coral reef terrain. This model, based on fractional Brownian motion (fBm), produced surfaces that were visually and statistically indistinguishable from natural seabeds, at spatial scales of 0.001–25 km². The conformity between model and nature allowed us to ascertain the importance of topography as a driver for the fractal patchiness that has been shown to occur in plan-view maps of reefscapes (e.g. Purkis et al. J Sediment Res 75:861–876, 2005, J Geol 115:493–508, 2007). For the considered Puerto Rican shelf, the necessary Brownian-like seabed topography likely arose through karst erosion overprinted by several episodes of reef development. Communicated by Geology Editor Dr. Bernhard Riegl     

Nonlinear EEG analysis based on a neural mass model

The well-known neural mass model described by Lopes da Silva et al. (1976) and Zetterberg et al. (1978) is fitted to actual EEG data. This is achieved by reformulating the original set of integral equations as a continuous-discrete state space model. The local linearization approach is then used to discretize the state equation and to construct a nonlinear Kalman filter. On this basis, a maximum likelihood procedure is used for estimating the model parameters for several EEG recordings. The analysis of the noise-free differential equations of the estimated models suggests that there are two different types of alpha rhythms: those with a point attractor and others with a limit cycle attractor. These attractors are also found by means of a nonlinear time series analysis of the EEG recordings. We conclude that the Hopf bifurcation described by Zetterberg et al. (1978) is present in actual brain dynamics. Received: 11 August 1997 / Accepted in revised form: 20 April 1999     

Dynamic updating of distributed neural representations using forward models

In this paper, we present a continuous attractor network model that we hypothesize will give some suggestion of the mechanisms underlying several neural processes such as velocity tuning to visual stimulus, sensory discrimination, sensorimotor transformations, motor control, motor imagery, and imitation. All of these processes share the fundamental characteristic of having to deal with the dynamic integration of motor and sensory variables in order to achieve accurate sensory prediction and/or discrimination. Such principles have already been described in the literature by other high-level modeling studies (Decety and Sommerville in Trends Cogn Sci 7:527–533, 2003; Oztop et al. in Neural Netw 19(3):254–271, 2006; Wolpert et al. in Philos Trans R Soc 358:593–602, 2003). With respect to these studies, our work is more concerned with biologically plausible neural dynamics at a population level. Indeed, we show that a relatively simple extension of the classical neural field models can endow these networks with additional dynamic properties for updating their internal representation using external commands. Moreover, an analysis of the interactions between our model and external inputs also shows interesting properties, which we argue are relevant for a better understanding of the neural processes of the brain.     

Relevance of nonlinear lumped-parameter models in the analysis of depth-EEG epileptic signals

In the field of epilepsy, the analysis of stereoelectroencephalographic (SEEG, intra-cerebral recording) signals with signal processing methods can help to better identify the epileptogenic zone, the area of the brain responsible for triggering seizures, and to better understand its organization. In order to evaluate these methods and to physiologically interpret the results they provide, we developed a model able to produce EEG signals from “organized” networks of neural populations. Starting from a neurophysiologically relevant model initially proposed by Lopes Da Silva et al. [Lopes da Silva FH, Hoek A, Smith H, Zetterberg LH (1974) Kybernetic 15: 27–37] and recently re-designed by Jansen et al. [Jansen BH, Zouridakis G, Brandt ME (1993) Biol Cybern 68: 275–283] the present study demonstrates that this model can be extended to generate spontaneous EEG signals from multiple coupled neural populations. Model parameters related to excitation, inhibition and coupling are then altered to produce epileptiform EEG signals. Results show that the qualitative behavior of the model is realistic; simulated signals resemble those recorded from different brain structures for both interictal and ictal activities. Possible exploitation of simulations in signal processing is illustrated through one example; statistical couplings between both simulated signals and real SEEG signals are estimated using nonlinear regression. Results are compared and show that, through the model, real SEEG signals can be interpreted with the aid of signal processing methods. Received: 3 January 2000 / Accepted: 24 March 2000     

Neither touch nor vision: sensory substitution as artificial synaesthesia?

Block (Trends Cogn Sci 7:285–286, 2003) and Prinz (PSYCHE 12:1–19, 2006) have defended the idea that SSD perception remains in the substituting modality (auditory or tactile). Hurley and Noë (Biol Philos 18:131–168, 2003) instead argued that after substantial training with the device, the perceptual experience that the SSD user enjoys undergoes a change, switching from tactile/auditory to visual. This debate has unfolded in something like a stalemate where, I will argue, it has become difficult to determine whether the perception acquired through the coupling with an SSD remains in the substituting or the substituted modality. Within this puzzling deadlock two new approaches have been recently suggested. Ward and Meijer (Conscious Cogn 19:492–500, 2010) describe SSD perception as visual-like but characterize it as a kind of artificially induced synaesthesia. Auvray et al. (Perception 36:416–430, 2007) and Auvray and Myin (Cogn Sci 33:1036–1058, 2009) suggest that SSDs let their users experience a new kind of perception. Deroy and Auvray (forthcoming) refine this position, and argue that this new kind of perception depends on pre-existing senses without entirely aligning with any of them. So, they have talked about perceptual experience in SSDs as going "beyond vision". In a similar vein, MacPherson (Oxford University Press, New York, 2011a) claims that “if the subjects (SSD users) have experiences with both vision-like and touch-like representational characteristics then perhaps they have a sense that ordinary humans do not” (MacPherson in Oxford University Press, New York, 2011a, p. 139).     

A tool for the prediction of structures of complex sugars

In two recent back to back articles(Xia et al., J Chem Theory Comput 3:1620–1628 and 1629–1643, 2007a, b) we have started to address the problem of complex oligosaccharide conformation and folding. The scheme previously presented was based on exhaustive searches in configuration space in conjunction with Nuclear Overhauser Effect (NOE) calculations and the use of a complex rotameric library that takes branching into account. NOEs are extremely useful for structural determination but only provide information about short range interactions and ordering. Instead, the measurement of residual dipolar couplings (RDC), yields information about molecular ordering or folding that is long range in nature. In this article we show the results obtained by incorporation RDC calculations into our prediction scheme. Using this new approach we are able to accurately predict the structure of six human milk sugars: LNF-1, LND-1, LNF-2, LNF-3, LNnT and LNT. Our exhaustive search in dihedral configuration space combined with RDC and NOE calculations allows for highly accurate structural predictions that, because of the non-ergodic nature of these molecules on a time scale compatible with molecular dynamics simulations, are extremely hard to obtain otherwise (Almond et al., Biochemistry 43:5853–5863, 2004). Molecular dynamics simulations in explicit solvent using as initial configurations the structures predicted by our algorithm show that the histo-blood group epitopes in these sugars are relatively rigid and that the whole family of oligosaccharides derives its conformational variability almost exclusively from their common linkage (β-d-GlcNAc-(1→3)-β-d-Gal) which can exist in two distinct conformational states. A population analysis based on the conformational variability of this flexible glycosidic link indicates that the relative population of the two distinct states varies for different human milk oligosaccharides. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Possible dynamic anchor points in a benzoxazinone derivative–human oxytocin receptor system — a molecular docking and dynamics calculation

In this study, we performed a molecular docking and dynamics simulation for a benzoxazinone–human oxytocin receptor system to determine the possible hydrophobic and electrostatic interaction points in the dynamic complex. After the homology modeling, the ligand was docked into the putative active using AutoDock 3.05. After the application of energetic and structural filters, the complexes obtained were further refined with a simulated annealing protocol (AMBER8) to remove steric clashes. Three complexes were selected for subjection to the molecular dynamics simulation (5 ns), and the results on the occurrence of average anchor points showed a stable complex between the benzoxazinone derivative and the receptor. The complex could be used as a good starting point for further analysis with site-directed mutagenesis, or further computational research. Figure The location of the ligands (complex B – blue; complex E – red; and complex F – green) in the transmembrane regions (TM1 – red; TM2 – blue; TM3 – yellow; TM4 – purple; TM5 – orange; TM6 – cyan; TM7 – pink) of the hOTR. For clarity, the EC and IC loops are not shown Electronic Supplementary Material Supplementary material is available at     

Kinetic models of photosystem II should accommodate the effect of donor side quenching on variable chlorophyll <Emphasis Type="Italic">a</Emphasis> fluorescence in the microseconds time range

Quantitative data on laser flash-induced variable fluorescence in the 100 ns to 1 ms time range (Belyaeva et al. in Photosynth Res 98:105–119, 2008) confirming those of others (Steffen et al. in Biochemistry 40:173–180, 2001, Biochemistry 44:3123–3132, 2005; Belyaeva et al. in Biophysics 51(6):976–990, 2006), need a substantial correction with respect to magnitude of the normalized variable fluorescence associated with single turnover-induced charge separation in RCs of PS II. Their data are conclusive with the involvement of donor side quenching, the release of which occurs with a rate constant in the range of tens of ms⁻¹, and presumed to be associated with reduction of Y_\textz ⁺ Y_{\text{z}}^{ + } by the OEC.     

Role of CAMKII in reinforcement learning: a computational model of glutamate and dopamine signaling pathways

Timely release of dopamine (DA) at the striatum seems to be important for reinforcement learning (RL) mediated by the basal ganglia. Houk et al. (in: Houk et al (eds) Models of information processing in the basal ganglia, (1995) proposed a cellular signaling pathway model to characterize the interaction between DA and glutamate pathways that have a role in RL. The model simulation results, using GENESIS KINETIKIT simulator, point out that there is not only prolongation of duration as proposed by Houk et al. (1995), but also an enhancement in the amplitude of autophosphorylation of CaMKII. Further, the autophosphorylated form of CaMKII may form a basis for the “eligibility trace” condition required in RL. This simulation study is the first of its kind to support the comprehensive theoretical proposal of Houk et al. (1995).     

TGF-Mediated Dynamics in a System of Many Coupled Nephrons

This paper presents a mathematical model of a system of many coupled nephrons branching from a common cortical radial artery, and accompanying analysis of that system. This modeling effort is a first step in understanding how coupling magnifies the tendency of nephrons to oscillate owing to tubuloglomerular feedback. Central to the present work is the single nephron integral model (as in Pitman et al., The IMA Volumes in Mathematics and Its Applications, vol. 129, pp. 345–364, 2002 and in Zaritski, Ph.D. Dissertation, 1999) which is a simplification of the single nephron PDE model of Layton et al. (Am. J. Physiol. 261, F904–F919, 1991). A second principal idea used in the present model is a coupling of model nephrons, generalizing the work of Pitman et al. (Bull. Math. Biol. 66, 1463–1492, 2004) who proposed a model of two coupled nephrons. In this study, we couple nephrons through a nearest neighbor interaction. Speaking generally, our results suggest that a series of similar nephrons coupled to their nearest neighbors are more prone to be found in an oscillatory mode, relative to a single nephron with the same properties. More specifically, we show analytically that, for N coupled identical nephrons, the region supporting oscillatory solutions in the time delay–gain parameter plane increases with N. Numerical simulations suggest that, if N nephrons have gains and time delays that do not differ by much, the system is, again, more prone to oscillate, relative to a single nephron, and the oscillations tend to be approximately synchronous and in-phase. We examine the effect of parameters on bifurcation. We also examine alternative models of coupling; this analysis allows us to conclude that the increased propensity of coupled nephrons to oscillate is a robust finding, true for several models of nephron interaction.     

Iron interference in the quantification of nitrate in soil extracts and its effect on hypothesized abiotic immobilization of nitrate

Human alteration of the nitrogen cycle has stimulated research on nitrogen cycling in many aquatic and terrestrial ecosystems, where analyses of nitrate (NO₃ ⁻) by standard laboratory methods are common. A recent study by Colman et al. (Biogeochemistry 84:161–169, 2007) identified a potential analytical interference of soluble iron (Fe) with NO₃ ⁻ quantification by standard flow-injection analysis of soil extracts, and suggested that this interference may have led Dail et al. (Biogeochemistry 54:131–146, 2001) to make an erroneous assessment of abiotic nitrate immobilization in prior ¹⁵N pool dilution studies of Harvard Forest soils. In this paper, we reproduce the Fe interference problem systematically and show that it is likely related to dissolved, complexed-Fe interfering with the colorimetric analysis of NO₂ ⁻. We also show how standard additions of NO₃ ⁻ and NO₂ ⁻ to soil extracts at native dissolved Fe concentrations reveal when the Fe interference problem occurs, and permit the assessment of its significance for past, present, and future analyses. We demonstrate low soluble Fe concentrations and good recovery of standard additions of NO₃ ⁻ and NO₂ ⁻ in extracts of sterilized Harvard Forest soils. Hence, we maintain that rapid NO₃ ⁻ immobilization occurred in sterilized samples of the Harvard Forest O horizon in the study by Dail et al. (2001). Furthermore, additional evidence is accumulating in the literature for rapid disappearance of NO₃ ⁻ added to soils, suggesting that our observations were not the result of an isolated analytical artifact. The conditions for NO₃ ⁻ reduction are likely to be highly dependent on microsite properties, both in situ and in the laboratory. The so-called “ferrous wheel hypothesis” (Davidson et al., Glob Chang Biol 9:228–236, 2003) remains an unproven, viable explanation for published observations.