Evidence against the Detectability of a Hippocampal Place Code Using Functional Magnetic Resonance Imaging

Individual hippocampal neurons selectively increase their firing rates in specific spatial locations. As a population, these neurons provide a decodable representation of space that is robust against changes to sensory- and path-related cues. This neural code is sparse and distributed, theoretically rendering it undetectable with population recording methods such as functional magnetic resonance imaging (fMRI). Existing studies nonetheless report decoding spatial codes in the human hippocampus using such techniques. Here we present results from a virtual navigation experiment in humans in which we eliminated visual- and path-related confounds and statistical limitations present in existing studies, ensuring that any positive decoding results would represent a voxel-place code. Consistent with theoretical arguments derived from electrophysiological data and contrary to existing fMRI studies, our results show that although participants were fully oriented during the navigation task, there was no statistical evidence for a place code

Finding the way with a noisy brain

Successful navigation is fundamental to the survival of nearly every animal on earth, and achieved by nervous systems of vastly different sizes and characteristics. Yet surprisingly little is known of the detailed neural circuitry from any species which can accurately represent space for navigation. Path integration is one of the oldest and most ubiquitous navigation strategies in the animal kingdom. Despite a plethora of computational models, from equational to neural network form, there is currently no consensus, even in principle, of how this important phenomenon occurs neurally. Recently, all path integration models were examined according to a novel, unifying classification system. Here we combine this theoretical framework with recent insights from directed walk theory, and develop an intuitive yet mathematically rigorous proof that only one class of neural representation of space can tolerate noise during path integration. This result suggests many existing models of path integration are not biologically plausible due to their intolerance to noise. This surprising result imposes significant computational limitations on the neurobiological spatial representation of all successfully navigating animals, irrespective of species. Indeed, noise-tolerance may be an important functional constraint on the evolution of neuroarchitectural plans in the animal kingdom

Isotropic-nematic transition in liquid crystals confined between rough walls

The effect of rough walls on the phase behaviour of a confined liquid crystal (LC) fluid is studied using constant pressure Monte Carlo simulations. The LC is modelled as a fluid of soft ellipsoidal molecules and the rough walls are represented as a hard wall with a number of molecules randomly embedded in them. It is found that the isotropic-nematic (IN) transition is shifted to higher pressures for rougher walls.Comment: 4 pages, 4 figures Accepted in Chemical Physics Letter

Alexithymia and posttraumatic stress disorder following epileptic seizure

This study investigated (1) the incidence of posttraumatic stress disorder following epileptic seizure (post-epileptic seizure PTSD) and psychiatric co-morbidity and (2) the extent to which alexithymia traits related to the severity of the preceding outcomes. Seventy-one people with epilepsy participated in the study and completed the Posttraumatic Stress Diagnostic Scale, Hospital Anxiety and Depression Scale (HADS), and Toronto Alexithymia Scale. The control group comprised 71 people without epilepsy who completed the HADS. Fifty-one percent met the diagnostic criteria for full-PTSD; 30 % for partial-PTSD and 19 % for no-PTSD. The epilepsy group reported significantly more anxiety and depression than the control with demographic variables controlled for. Difficulty identifying feelings predicted post-epileptic seizure PTSD, anxiety and depression. It was positively correlated with post-epileptic seizure PTSD and depression, while it was negatively correlated with anxiety. People can develop PTSD and psychiatric co-morbid symptoms following epileptic seizures. The severity of these symptoms was related to difficulty in identifying internal feelings and emotions. © 2012 Springer Science+Business Media New York

DeFINE: Delayed Feedback based Immersive Navigation Environment for Studying Goal-Directed Human Navigation

With the advent of consumer-grade products for presenting an immersive virtual environment (VE), there is a growing interest in utilizing VEs for testing human navigation behavior. However, preparing a VE still requires a high level of technical expertise in computer graphics and virtual reality, posing a significant hurdle to embracing the emerging technology. To address this issue, this paper presents Delayed Feedback based Immersive Navigation Environment (DeFINE), a framework that allows for easy creation and administration of navigation tasks within customizable VEs via intuitive graphical user interfaces and simple settings files. Importantly, DeFINE has a built-in capability to provide performance feedback to participants during an experiment, a feature that is critically missing in other similar frameworks. To show the usability of DeFINE from both experimentalists' and participants' perspectives, a demonstration was made in which participants navigated to a hidden goal location with feedback that differentially weighted speed and accuracy of their responses. In addition, the participants evaluated DeFINE in terms of its ease of use, required workload, and proneness to induce cybersickness. The demonstration exemplified typical experimental manipulations DeFINE accommodates and what types of data it can collect for characterizing participants' task performance. With its out-of-the-box functionality and potential customizability due to open-source licensing, DeFINE makes VEs more accessible to many researchers.Comment: 43 pages, 10 figures, 5 tables, Submitted to Behavioral Research Method

The growth of linear perturbations in generic defect models for structure formation

We study the growth of linear perturbations induced by a generic causal scaling source as a function of the cosmological parameters $h$, $\Omega^m_0$ and $\Omega^\Lambda_0$. We show that for wavenumbers k \gsim 0.01 h/Mpc the spectrum of density and velocity perturbations scale in a similar way to that found in inflationary models with primordial perturbations. We show that this result is independent of the more or less incoherent nature of the source, the small scale power spectrum of the source and of deviations from scaling which naturally occur at late times if $\Omega^m_0 \neq 1$.Comment: 4 pages, 2 figure

Structure of a liquid crystalline fluid around a macroparticle: Density functional theory study

The structure of a molecular liquid, in both the nematic liquid crystalline and isotropic phases, around a cylindrical macroparticle, is studied using density functional theory. In the nematic phase the structure of the fluid is highly anisotropic with respect to the director, in agreement with results from simulation and phenomenological theories. On going into the isotropic phase the structure becomes rotationally invariant around the macroparticle with an oriented layer at the surface.Comment: 10 pages, 6 figues. Submitted to Phys. Rev.

Action Potential Waveform Variability Limits Multi-Unit Separation in Freely Behaving Rats

Extracellular multi-unit recording is a widely used technique to study spontaneous and evoked neuronal activity in awake behaving animals. These recordings are done using either single-wire or mulitwire electrodes such as tetrodes. In this study we have tested the ability of single-wire electrodes to discriminate activity from multiple neurons under conditions of varying noise and neuronal cell density. Using extracellular single-unit recording, coupled with iontophoresis to drive cell activity across a wide dynamic range, we studied spike waveform variability, and explored systematic differences in single-unit spike waveform within and between brain regions as well as the influence of signal-to-noise ratio (SNR) on the similarity of spike waveforms. We also modelled spike misclassification for a range of cell densities based on neuronal recordings obtained at different SNRs. Modelling predictions were confirmed by classifying spike waveforms from multiple cells with various SNRs using a leading commercial spike-sorting system. Our results show that for single-wire recordings, multiple units can only be reliably distinguished under conditions of high recording SNR (≥4) and low neuronal density (≈20,000/ mm3). Physiological and behavioural changes, as well as technical limitations typical of awake animal preparations, reduce the accuracy of single-channel spike classification, resulting in serious classification errors. For SNR <4, the probability of misclassifying spikes approaches 100% in many cases. Our results suggest that in studies where the SNR is low or neuronal density is high, separation of distinct units needs to be evaluated with great caution

Cosmic strings, loops, and linear growth of matter perturbations

We describe the detailed study and results of high-resolution numerical simulations of string-induced structure formation in open universes and those with a non-zero cosmological constant. The effect from small loops generated from the string network has also been investigated. We provide a semi-analytical model which can reproduce these simulation results. A detailed study of cosmic string network properties regarding structure formation is also given, including the correlation time, the topological analysis of the source spectrum, the correlation between long strings and loops, and the evolution of long-string and loop energy densities. For models with $\Gamma=\Omega h=0.1--0.2 and a cold dark matter background, we show that the linear density fluctuation power spectrum induced by cosmic strings has both an amplitude at$8 h^{-1}$Mpc,$\sigma_8$, and an overall shape which are consistent within uncertainties with those currently inferred from galaxy surveys. The cosmic string scenario with hot dark matter requires a strongly scale-dependent bias in order to agree with observations.Comment: 60 pages, 24 figure

Integration-free reprogramming of lamina propria progenitor cells

Producing induced pluripotent stem cells (iPSCs) from human tissue for use in personalized medicine strategies or therapeutic testing is at the forefront of medicine. Therefore, identifying a source of cells to reprogram that is easily accessible via a simple noninvasive procedure is of great clinical importance. Reprogramming these cells to iPSCs through nonintegrating methods for genetic manipulation is paramount for regenerative purposes. Here, we demonstrate reprogramming of oral mucosal lamina propria progenitor cells from patients undergoing routine dental treatment. Reprogramming was performed utilizing nonintegrating plasmids containing all 6 pluripotency genes (OCT4, SOX2, KLF4, NANOG, LIN28, and cMYC). Resulting iPSCs lacked genetic integration of the vector genes and had the ability to differentiate down mesoderm, ectoderm, and endoderm lineages, demonstrating pluripotency. In conclusion, oral mucosal lamina propria progenitor cells represent a source of cells that can be obtained with minimal invasion, as they can be taken concurrently with routine treatments. The resulting integration-free iPSCs therefore have great potential for use in personalized medicine strategies