Mouse tracking performance: A new approach to analyzing continuous mouse tracking data.

Mouse tracking is an important source of data in cognitive science. Most contemporary mouse tracking studies use binary-choice tasks and analyze the curvature or velocity of an individual mouse movement during an experimental trial as participants select from one of the two options. However, there are many types of mouse tracking data available beyond what is produced in a binary-choice task, including naturalistic data from web users. In order to utilize these data, cognitive scientists need tools that are robust to the lack of trial-by-trial structure in most normal computer tasks. We use singular value decomposition (SVD) and detrended fluctuation analysis (DFA) to analyze whole time series of unstructured mouse movement data. We also introduce a new technique for describing two-dimensional mouse traces as complex-valued time series, which allows SVD and DFA to be applied in a straightforward way without losing important spatial information. We find that there is useful information at the level of whole time series, and we use this information to predict performance in an online task. We also discuss how the implications of these results can advance the use of mouse tracking research in cognitive science.

Radiance backscattered by a strongly scattering medium in the high spatial frequency limit.

We study the radiative transfer of a spatially modulated plane wave incident on a half-space composed of a uniformly scattering and absorbing medium. For spatial frequencies that are large compared to the scattering coefficient, we find that first-order scattering governs the leading behavior of the radiance backscattered by the medium. The first-order scattering approximation reveals a specific curve on the backscattered hemisphere where the radiance is concentrated. Along this curve, the radiance assumes a particularly simple expression that is directly proportional to the phase function. These results are inherent to the radiative transfer equation at large spatial frequency and do not have a strong dependence on any particular optical property. Consequently, these results provide the means by which spatial frequency domain imaging technologies can directly measure the phase function of a sample. Numerical simulations using the discrete ordinate method along with the source integration interpolation method validate these theoretical findings.

Modeling broadband cloaking using 3D nano-assembled plasmonic meta-structures.

The concept of "cloaking" an object is a very attractive one, especially in the visible (VIS) and near infra-red (NIR) regions of the electromagnetic spectrum, as that would reduce the visibility of an object to the eye. One possible route to achieving this goal is by leveraging the plasmonic property of metallic nanoparticles (NPs). We model and simulate light in the VIS and NIR scattered by a core of a homogeneous medium, covered by plasmonic cloak that is a spherical shell composed of gold nanoparticles (AuNPs). To consider realistic, scalable, and robust plasmonic cloaks that are comparable, or larger, in size to the wavelength, we introduce a multiscale simulation platform. This model uses the multiple scattering theory of Foldy and Lax to model interactions of light with AuNPs combined with the method of fundamental solutions to model interactions with the core. Numerical results of our simulations for the scattering cross-sections of core-shell composite indicate significant scattering suppression of up to 50% over a substantial portion of the desired spectral range (400 - 600 nm) for cores as large as 900 nm in diameter by a suitable combination of AuNP sizes and filling fractions of AuNPs in the shell.

Intensity-only inverse scattering with MUSIC.

We present a method for inverse scattering that relies on intensity-only measurements of the scattered field on a single measurement plane. By collecting measurements from a suite of experiments in which the sample is illuminated using different incident fields, we create sufficient data diversity to overcome the limitations of the intensity-only measurements. We give an explicit procedure that uses an algebraic relation called the polarization identity to convert intensity measurements of scattered fields to interferometric measurements in which one of the scattered fields serves as the reference. By adjusting the multiple signal classification (MUSIC) method for these interferometric data, we effectively recover the location and shapes of multiple objects contained in the imaging region. This method is effective and robust to noise as long as there is sufficiently high data diversity and the fractional volume of the scattering objects is not too high. We present image reconstructions for several three-dimensional examples with simulated data computed using the Method of Fundamental Solutions that demonstrate the effectiveness of this imaging method.

Quantitative subsurface imaging in strongly scattering media.

We present a method to obtain quantitatively accurate images of small obstacles or inhomogeneities situated near the surface of a strongly scattering medium. The method uses time-resolved measurements of backscattered light to form the images. Using the asymptotic solution of the radiative transfer equation for this problem, we determine that the key information content in measurements is modeled by a diffusion approximation that is valid for small source-detector distances, and shallow penetration depths. We simplify this model further by linearizing the effect of the inhomogeneities about the known background optical properties using the Born approximation. The resulting model is used in a two-stage imaging algorithm. First, the spatial location of the inhomogeneities are determined using a modification of the multiple signal classification (MUSIC) method. Using those results, we then determine the quantitative values of the inhomogeneities through a least-squares approximation. We find that this two-stage method is most effective for reconstructing a sequence of one-dimensional images along the penetration depth corresponding to null source-detector separations rather than simultaneously using measurements over several source-detector distances. This method is limited to penetration depths and distances between boundary measurements on the order of the scattering mean-free path.

Generalized Kubelka-Munk approximation for multiple scattering of polarized light.

We introduce a new model for multiple scattering of polarized light by statistically isotropic and mirror-symmetric particles, which we call the generalized Kubelka-Munk (gKM) approximation. It is obtained through a linear transformation of the system of equations resulting from applying the double spherical harmonics approximation of order one to the vector radiative transfer equation (vRTE). The result is a 32×32 system of differential equations that is much simpler than the vRTE. We compare numerical solutions of the vRTE with the gKM approximation for the problem in which a plane wave is normally incident on a plane-parallel slab composed of a uniform absorbing and scattering medium. These comparisons show that the gKM approximation accurately captures the key features of the polarization state of multiply scattered light. In particular, the gKM approximation accurately captures the complicated polarization characteristics of light backscattered by an optically thick medium composed of a monodisperse distribution of dielectric spheres over a broad range of sphere sizes.

Asymptotic theory of circular polarization memory.

We establish a quantitative theory of circular polarization memory, which is the unexpected persistence of the incident circular polarization state in a strongly scattering medium. Using an asymptotic analysis of the three-dimensional vector radiative transfer equation (VRTE) in the limit of strong scattering, we find that circular polarization memory must occur in a boundary layer near the portion of the boundary on which polarized light is incident. The boundary layer solution satisfies a one-dimensional conservative scattering VRTE. Through a spectral analysis of this boundary layer problem, we introduce the dominant mode, which is the slowest-decaying mode in the boundary layer. To observe circular polarization memory for a particular set of optical parameters, we find that this dominant mode must pass three tests: (1) this dominant mode is given by the largest, discrete eigenvalue of a reduced problem that corresponds to Fourier mode k=0 in the azimuthal angle, and depends only on Stokes parameters U and V; (2) the polarization state of this dominant mode is largely circular polarized so that |V|≫|U|; and (3) the circular polarization of this dominant mode is maintained for all directions so that V is sign-definite. By applying these three tests to numerical calculations for monodisperse distributions of Mie scatterers, we determine the values of the size and relative refractive index when circular polarization memory occurs. In addition, we identify a reduced, scalar-like problem that provides an accurate approximation for the dominant mode when circular polarization memory occurs.

Forward-peaked scattering of polarized light: erratum.

We intend to correct the typographical errors that occurred in our recent Letter [Opt. Lett.39, 6422 (2014)].

Extending generalized Kubelka-Munk to three-dimensional radiative transfer.

The generalized Kubelka-Munk (gKM) approximation is a linear transformation of the double spherical harmonics of order one (DP1) approximation of the radiative transfer equation. Here, we extend the gKM approximation to study problems in three-dimensional radiative transfer. In particular, we derive the gKM approximation for the problem of collimated beam propagation and scattering in a plane-parallel slab composed of a uniform absorbing and scattering medium. The result is an 8×8 system of partial differential equations that is much easier to solve than the radiative transfer equation. We compare the solutions of the gKM approximation with Monte Carlo simulations of the radiative transfer equation to identify the range of validity for this approximation. We find that the gKM approximation is accurate for isotropic scattering media that are sufficiently thick and much less accurate for anisotropic, forward-peaked scattering media.

Forward-peaked scattering of polarized light.

Polarized light propagation in a multiple scattering medium is governed by the vector radiative transfer equation. We analyze the vector radiative transfer equation in asymptotic limit of forward-peaked scattering and derive an approximate system of equations for the Stokes parameters, which we call the vector Fokker-Planck approximation. The vector Fokker-Planck approximation provides valuable insight into several outstanding issues regarding the forward-peaked scattering of polarized light such as the polarization memory phenomenon.

Deriving Kubelka-Munk theory from radiative transport.

We derive Kubelka-Munk (KM) theory systematically from the radiative transport equation (RTE) by analyzing the system of equations resulting from applying the double spherical harmonics method of order one and transforming that system into one governing the positive- and negative-going fluxes. Through this derivation, we establish the theoretical basis of KM theory, identify all parameters, and determine its range of validity. Moreover, we are able to generalize KM theory to take into account general boundary sources and nonhomogeneous terms, for example. The generalized Kubelka-Munk (gKM) equations are also much more accurate at approximating the solution of the RTE. We validate this theory through comparison with numerical solutions of the RTE.

Hashtags as signals of political identity: #BlackLivesMatter and #AllLivesMatter.

We investigate perceptions of tweets marked with the #BlackLivesMatter and #AllLivesMatter hashtags, as well as how the presence or absence of those hashtags changed the meaning and subsequent interpretation of tweets in U.S. participants. We found a strong effect of partisanship on perceptions of the tweets, such that participants on the political left were more likely to view #AllLivesMatter tweets as racist and offensive, while participants on the political right were more likely to view #BlackLivesMatter tweets as racist and offensive. Moreover, we found that political identity explained evaluation results far better than other measured demographics. Additionally, to assess the influence of hashtags themselves, we removed them from tweets in which they originally appeared and added them to selected neutral tweets. Our results have implications for our understanding of how social identity, and particularly political identity, shapes how individuals perceive and engage with the world.

Modeling the diffuse reflectance due to a narrow beam incident on a turbid medium.

We present a model for the diffuse reflectance when a continuous beam is incident normally on a half space composed of a uniform scattering and absorbing medium. This model is the result of an asymptotic analysis of the radiative transport equation for strong scattering, weak absorption, and a narrow beam width. Through comparison with the diffuse reflectance computed using the numerical solution of the radiative transport equation, we show that this diffuse reflectance model gives results that are accurate for small source--detector separation distances.

Combining diffuse optical tomography and spectroscopy to detect and characterize lesions in two-layered tissues.

We combine diffuse optical tomography for detecting and localizing an inhomogeneity in a two-layered tissue and diffuse optical spectroscopy (DOS) for characterizing the spectrum of that inhomogeneity. For detecting and localizing an inhomogeneity, we reduce the number of unknowns substantially by seeking only the location and size of the inhomogeneity. Then, we seek to recover an unknown specific tumor component of that inhomogeneity from spectral data. In doing so, we develop a method for distinguishing between healthy and tumorous lesions. We demonstrate the utility of this theory with numerical simulations.

Medical Workflow Design and Planning Using Node-RED Data Fusion.

The space of clinical planning requires a complex arrangement of information, often not capable of being captured in a singular dataset. As a result, data fusion techniques can be used to combine multiple data sources as a method of enriching data to mimic and compliment the nature of clinical planning. These techniques are capable of aiding healthcare providers to produce higher quality clinical plans and better progression monitoring techniques. Clinical planning and monitoring are important facets of healthcare which are essential to improving the prognosis and quality of life of patients with chronic and debilitating conditions such as COPD. To exemplify this concept, we utilize a Node-Red-based clinical planning and monitoring tool that combines data fusion techniques using the JDL Model for data fusion and a domain specific language which features a self-organizing abstract syntax tree.

Correcting the diffusion approximation at the boundary.

The diffusion approximation to the radiative transport equation applies for light that has propagated deeply into an optically thick medium, such as biological tissue. It does not accurately model light near boundaries where measurements of scattered light are often taken. Here, we compute a correction to the diffusion approximation at the boundary. This correction requires only small modifications to the standard diffusion approximation used in biomedical optics. In particular, one needs only to compute the coefficients in the boundary condition for the diffusion approximation and an additive correction. We give explicit procedures for these computations. Using numerical results for the steady-state plane-parallel slab problem, we show that this corrected diffusion approximation is a much better approximation than the standard diffusion approximation for modeling the reflectance and transmittance.

Scattering of light by molecules over a rough surface.

We present a theory for the multiple scattering of light by obstacles situated over a rough surface. This problem is important for applications in biological and chemical sensors. To keep the formulation of this theory simple, we study scalar waves. This theory requires knowledge of the scattering operator (t-matrix) for each of the obstacles as well as the reflection operator for the rough surface. The scattering operator gives the field scattered by the obstacle due to an exciting field incident on the scatterer. The reflection operator gives the field reflected by the rough surface due to an exciting field incident on the rough surface. We apply this general theory for the special case of point scatterers and a slightly rough surface with homogeneous Dirichlet and Neumann boundary conditions. We show examples that demonstrate the utility of this theory.

Comparison of light scattering models for diffuse optical tomography.

We reconstruct images of the absorption and the scattering coefficients for diffuse optical tomography using five different models for light propagation in tissues: (1) the radiative transport equation, (2) the delta-Eddington approximation, (3) the Fokker-Planck approximation, (4) the Fokker-Planck-Eddington approximation and (5) the generalized Fokker-Planck-Eddington approximation. The last four models listed are approximations of the radiative transport equation that take into account forward-peaked scattering analytically. Using simulated data from the numerical solution of radiative transport equation, we solve the inverse problem for the absorption and scattering coefficients using the transport-backtransport method. Through comparison of the numerical results, we show that all of these light scattering models produce good image reconstructions. In addition, we show that these approximations afford considerable computational savings over solving the radiative transport equation. However, all of the models exhibit significant "cross-talk" between absorption and scattering coefficient images. Among the approximations, we have found that the generalized Fokker-Planck-Eddington equation produced the best image reconstructions in comparison with the image reconstructions produced by the radiative transport equation.

Multimodal Analgesia for Perioperative Management of Patients presenting for Spinal Surgery.

Multimodal, non-opioid based analgesia has become the cornerstone of ERAS protocols for effective analgesia after spinal surgery. Opioid side effects, dependence and legislation restricting long term opioid use has led to a resurgence in interest in opioid sparing techniques. The increasing array of multimodal opioid sparing analgesics available for spinal surgery targeting novel receptors, transmitters, and altering epigenetics can help provide an optimal perioperative experience with less opioid side effects and long-term dependence. Epigenetic mechanisms of pain may enhance or suppress gene expression, without altering the genome itself. Such mechanisms are complex, dynamic and responsive to environment. Alterations that occur can affect the pathophysiology of pain management at a DNA level, modifying perceived pain relief. In this review, we provide a brief overview of epigenetics of pain, systemic local anesthetics and neuraxial techniques that continue to remain useful for spinal surgery, neuropathic agents, as well as other common and less common target receptors for a truly multimodal approach to perioperative pain management.

Light transport in two-layer tissues.

We study theoretically light backscattered by tissues using the radiative transport equation. In particular we consider a two-layered medium in which a finite slab is situated on top of a half space. We solve the one-dimensional problem in which a plane wave is incident normally on the top layer and is the only source of light. The solution to this problem is obtained formally by imposing continuity between the solutions for the upper and lower layers. However, we are interested solely in probing the top layer. Assuming that the optical properties in the lower layer are known, we remove it from the problem yielding a finite slab problem by prescribing an alternate boundary condition. This boundary condition is derived using the theory of Green's functions and is exact. Hence, one needs only to solve the transport equation in a finite slab using this alternate boundary condition. We derive an asymptotic solution for the case when the slab is optically thin. We extend these results to the three-dimensional problem using Fourier transforms. These results are validated by comparisons with numerical solutions for the entire two-layered problem.