The statistics of lines in natural images and implications for visual detection

As borders between different regions, lines are an important element of natural images. Already at the level of the mammalian primary visual cortex (V1), neurons respond best to oriented bars. We reduce a set of images to linear segments and analyze their statistical properties. In particular, appropriately defined Fourier spectra show more power in their transverse component than in the longitudinal one. We then characterize filters that are best suited for extracting information from such images, and find some qualitative consistency with neural connections in V1. We also demonstrate that such filters are efficient in reconstructing missing lines in an image.     

Synchrony between orientation-selective neurons is modulated during adaptation-induced plasticity in cat visual cortex

Background  

Visual neurons respond essentially to luminance variations occurring within their receptive fields. In primary visual cortex, each neuron is a filter for stimulus features such as orientation, motion direction and velocity, with the appropriate combination of features eliciting maximal firing rate. Temporal correlation of spike trains was proposed as a potential code for linking the neuronal responses evoked by various features of a same object. In the present study, synchrony strength was measured between cells following an adaptation protocol (prolonged exposure to a non-preferred stimulus) which induce plasticity of neurons' orientation preference.     

Developmental and neurochemical features of cholinergic neurons in the murine cerebral cortex

Background  

The existence and role of intrinsic cholinergic cells in the cerebral cortex is controversial, because of their variable localization and morphology in different mammalian species. We have applied choline acetyltransferase (ChAT) immunocytochemistry to study the distribution of cholinergic neurons in the murine cerebral cortex, in the adult and during postnatal development. For more precise neurochemical identification of these neurons, the possible colocalization of ChAT with different markers of cortical neuronal populations has been analyzed by confocal microscopy. This method was also used to verify the relationship between cholinergic cells and cortical microvessels.     

Scale-invariance of receptive field properties in primary visual cortex

Background  

Our visual system enables us to recognize visual objects across a wide range of spatial scales. The neural mechanisms underlying these abilities are still poorly understood. Size- or scale-independent representation of visual objects might be supported by processing in primary visual cortex (V1). Neurons in V1 are selective for spatial frequency and thus represent visual information in specific spatial wavebands. We tested whether different receptive field properties of neurons in V1 scale with preferred spatial wavelength. Specifically, we investigated the size of the area that enhances responses, i.e., the grating summation field, the size of the inhibitory surround, and the distance dependence of signal coupling, i.e., the linking field.     

Symmetry induced coupling of cortical feature maps

The mammalian visual cortex maps retinal position (retinotopy) and orientation preference (OP) across its surface. Simultaneous measurements in vivo suggest that positive correlation exists between the location of dislocations in these two maps, contradicting the predictions of classical dimension reduction models. Model symmetries exert a significant influence on pattern development. However, classical models for cortical map formation have inappropriate symmetry properties. By applying equivariant bifurcation theory we derive symmetry induced, model independent coupling of the OP and retinotopic maps and show that this coupling replicates observations.     

Different ocular dominance map formation influenced by orientation preference columns in visual cortices

In animal experiments, the observed orientation preference and ocular dominance columns in the visual cortex of the brain show various pattern types. Here, we show that the different visual map formations in various species are due to the crossover behavior in anisotropic systems composed of orientational and scalar components such as easy-plane Heisenberg models. We predict the transition boundary between different pattern types with the anisotropy as a main bifurcation parameter, which is consistent with experimental observations.     

Elucidating a normal function of huntingtin by functional and microarray analysis of huntingtin-null mouse embryonic fibroblasts

Background

Multi-sensory integration is necessary for organisms to discriminate different environmental stimuli and thus determine behavior. Caenorhabditis elegans has 12 pairs of amphid sensory neurons, which are involved in generating behaviors such as thermotaxis toward cultivation temperature, and chemotaxis toward chemical stimuli. This arrangement of known sensory neurons and measurable behavioral output makes C. elegans suitable for addressing questions of multi-sensory integration in the nervous system. Previous studies have suggested that C. elegans can process different chemoattractants simultaneously. However, little is known about how these organisms can integrate information from stimuli of different modality, such as thermal and chemical stimuli.

Results

We studied the behavior of a population of C. elegans during simultaneous presentation of thermal and chemical stimuli. First, we examined thermotaxis within the radial temperature gradient produced by a feedback-controlled thermoregulator. Separately, we examined chemotaxis toward sodium chloride or isoamyl alcohol. Then, assays for simultaneous presentations of 15°C (colder temperature than 20°C room temperature) and chemoattractant were performed with 15°C-cultivated wild-type worms. Unlike the sum of behavioral indices for each separate behavior, simultaneous presentation resulted in a biased migration to cold regions in the first 10 min of the assay, and sodium chloride-regions in the last 40 min. However, when sodium chloride was replaced with isoamyl alcohol in the simultaneous presentation, the behavioral index was very similar to the sum of separate single presentation indices. We then recorded tracks of single worms and analyzed their behavior. For behavior toward sodium chloride, frequencies of forward and backward movements in simultaneous presentation were significantly different from those in single presentation. Also, migration toward 15°C in simultaneous presentation was faster than that in 15°C-single presentation.

Conclusion

We conclude that worms preferred temperature to chemoattractant at first, but preferred the chemoattractant sodium chloride thereafter. This preference was not seen for isoamyl alcohol presentation. We attribute this phase-dependent preference to the result of integration of thermosensory and chemosensory signals received by distinct sensory neurons.     

Structural effects and potential changes in growth factor signalling in penis-projecting autonomic neurons after axotomy

Background  

The responses of adult parasympathetic ganglion neurons to injury and the neurotrophic mechanisms underlying their axonal regeneration are poorly understood. This is especially relevant to penis-projecting parasympathetic neurons, which are vulnerable to injury during pelvic surgery such as prostatectomy. We investigated the changes in pelvic ganglia of adult male rats in the first week after unilateral cavernous (penile) nerve axotomy (cut or crush lesions). In some experiments FluoroGold was injected into the penis seven days prior to injury to allow later identification of penis-projecting neurons. Neurturin and glial cell line-derived neurotrophic factor (GDNF) are neurotrophic factors for penile parasympathetic neurons, so we also examined expression of relevant receptors, GFRα1 and GFRα2, in injured pelvic ganglion neurons.     

Hierarchical features of large-scale cortical connectivity

The analysis of complex networks has revealed patterns of organization in a variety of natural and artificial systems, including neuronal networks of the brain at multiple scales. In this paper, we describe a novel analysis of the large-scale connectivity between regions of the mammalian cerebral cortex, utilizing a set of hierarchical measurements proposed recently. We examine previously identified functional clusters of brain regions in macaque visual cortex and cat cortex and find significant differences between such clusters in terms of several hierarchical measures, revealing differences in how these clusters are embedded in the overall cortical architecture. For example, the ventral cluster of visual cortex maintains structurally more segregated, less divergent connections than the dorsal cluster, which may point to functionally different roles of their constituent brain regions.     

IR Absorption,Raman Scattering,and IR-Vis Sum-Frequency Generation Spectroscopy as Quantitative Probes of Surface Structure

Abstract:Vibrational spectroscopy is a valuable quantitative tool for the determination of structure at surfaces. Various techniques may be applicable and useful, depending on what is available, the transparency of the substrates, the need for in situ probes, and the degree of interfacial specificity required. We examine and compare signals in infrared absorption, Raman scattering, and vibrational sum-frequency generation spectroscopy to the underlying molecular response. In all of these experiments, varying the beam polarizations enables the orientation of specific chemical functional groups to be determined. However, the sensitivity of each technique is directly connected to the manner in which the molecular response manifests itself in the measured signal. Starting with simple distributions of a single vibrational mode, leading up to multiple vibrational bands in more complex orientation distributions, we compare these three techniques in terms of their sensitivity to features of the molecular orientation distribution. This review is aimed at guiding planned experiments when multiple techniques are available for surface structural analysis.     

Scaling properties of image textures: A detrending fluctuation analysis approach

The aim of this paper is to explore the application of detrended fluctuation analysis (DFA) to study roughness features of images. Unidimensional sequences at different image orientations are extracted and their average scaling exponent is estimated. In this form, the existence of anisotropies can be detected when considerable variations in the scaling exponent at different image orientation are observed. Different images from grass to solar granulation are analyzed and the underlying physics of such results is briefly commented.     

Random waves in the brain: Symmetries and defect generation in the visual cortex

How orientation maps in the visual cortex of the brain develop is a matter of long standing debate. Experimental and theoretical evidence suggests that their development represents an activity-dependent self-organization process. Theoretical analysis [1] exploring this hypothesis predicted that maps at an early developmental stage are realizations of Gaussian random fields exhibiting a rigorous lower bound for their densities of topological defects, called pinwheels. As a consequence, lower pinwheel densities, if observed in adult animals, are predicted to develop through the motion and annihilation of pinwheel pairs. Despite of being valid for a large class of developmental models this result depends on the symmetries of the models and thus of the predicted random field ensembles. In [1] invariance of the orientation map's statistical properties under independent space rotations and orientation shifts was assumed. However, full rotation symmetry appears to be broken by interactions of cortical neurons, e.g. selective couplings between groups of neurons with collinear orientation preferences [2]. A recently proposed new symmetry, called shift-twist symmetry [3], stating that spatial rotations have to occur together with orientation shifts in order to be an appropriate symmetry transformation, is more consistent with this organization. Here we generalize our random field approach to this important symmetry class. We propose a new class of shift-twist symmetric Gaussian random fields and derive the general correlation functions of this ensemble. It turns out that despite strong effects of the shift-twist symmetry on the structure of the correlation functions and on the map layout the lower bound on the pinwheel densities remains unaffected, predicting pinwheel annihilation in systems with low pinwheel densities.     

The effects of neuron heterogeneity and connection mechanism in cortical networks

The mammalian cortices show an specific architecture close to the optimum, represented by the high clustering, short processing steps and short wiring length. What are the key factors that influence the layout of neural connectivity networks? Here a model to investigate the conditions leading to the small-world cortical networks with minimal global wiring is presented. The essential factors in this model are the introductions of the unequal number distribution of heterogeneous neurons and two connection mechanisms, the preferential attachment to neurons with large spatial coverage (PANLSC) and distance preference. Outcomes show that the specific architecture close to the optimum can only result from the PANLSC when the number distribution of neurons with diverse spatial coverage is highly unequal. This suggests the PANLSC may be an important connection mechanism in cortical systems.     

Neuronal avalanches and coherence potentials

The mammalian cortex consists of a vast network of weakly interacting excitable cells called neurons. Neurons must synchronize their activities in order to trigger activity in neighboring neurons. Moreover, interactions must be carefully regulated to remain weak (but not too weak) such that cascades of active neuronal groups avoid explosive growth yet allow for activity propagation over long-distances. Such a balance is robustly realized for neuronal avalanches, which are defined as cortical activity cascades that follow precise power laws. In experiments, scale-invariant neuronal avalanche dynamics have been observed during spontaneous cortical activity in isolated preparations in vitro as well as in the ongoing cortical activity of awake animals and in humans. Theory, models, and experiments suggest that neuronal avalanches are the signature of brain function near criticality at which the cortex optimally responds to inputs and maximizes its information capacity. Importantly, avalanche dynamics allow for the emergence of a subset of avalanches, the coherence potentials. They emerge when the synchronization of a local neuronal group exceeds a local threshold, at which the system spawns replicas of the local group activity at distant network sites. The functional importance of coherence potentials will be discussed in the context of propagating structures, such as gliders in balanced cellular automata. Gliders constitute local population dynamics that replicate in space after a finite number of generations and are thought to provide cellular automata with universal computation. Avalanches and coherence potentials are proposed to constitute a modern framework of cortical synchronization dynamics that underlies brain function.     

A method to predict the orientation relationship,interface planes and morphology between a crystalline precipitate and matrix. Part I. Approach

A model based on the near-coincidence of diffraction intensity weighted reciprocal-lattice spots is proposed to determine preferred orientation relationships between two crystalline phases. The preferred orientation is found by minimizing the three-dimensional lattice mismatch, i.e. by maximizing the total overlapping intensity, between the diffraction spots of two crystals. The procedure is biased towards matching reciprocal lattice sites with high structure-factor values, which is physically equivalent to matching planes of high atomic density. In contrast to previous reciprocal-lattice models, including the diffraction intensity in the present method makes it sensitive to the types of atoms in (chemistry of) crystals. The preferred orientation relationship is then used to identify the orientations of low-energy interfaces using a Δ g approach. A Voronoi (or Wigner–Seitz) construction based on the Δ g values is further used to qualitatively estimate the equilibrium shape of the precipitate in the matrix. The model was tested by performing calculations on hypothetical Au–Cu crystals to investigate the effects of chemistry and fcc truncated-octahedral precipitates in fcc matrices in Al–Ag, Al–Xe and Al–Pb alloys. The present model has the ability to sample the entire orientation space and rationalize and compare alternate orientation relationships in a reasonable timeframe, thereby providing insight into the formation of precipitate orientation relationships and shapes.     

Electroencephalograms in epilepsy: analysis and seizure prediction within the framework of Lyapunov theory

Epileptic seizures are defined as the clinical manifestation of excessive and hypersynchronous activity of neurons in the cerebral cortex and represent one of the most frequent malfunctions of the human central nervous system. Therefore, the search for precursors and predictors of a seizure is of utmost clinical relevance and may even guide us to a deeper understanding of the seizure generating mechanisms. We extract chaos-indicators such as Lyapunov exponents and Kolmogorov entropies from different types of electroencephalograms (EEGs): this covers mainly intracranial EEGs (semi-invasive and invasive recording techniques), but also scalp-EEGs from the surface of the skin. Among the analytical methods we tested up to now, we find that the spectral density of the local expansion exponents is best suited to predict the onset of a forthcoming seizure. We also evaluate the time-evolution of the dissipation in these signals: it exhibits strongly significant variations that clearly relate to the time relative to a seizure onset. This article is mainly devoted to an assessment of these methods with respect to their sensitivity to EEG changes, e.g., prior to a seizure. Further, we investigate interictal EEGs (i.e., far away from a seizure) in order to characterize their more general properties, such as the convergence of the reconstructed quantities with respect to the number of phase space dimensions. Generally we use multichannel reconstruction, but we also present a comparison with the delay-embedding technique.     

Thomas precession: Its underlying gyrogroup axioms and their use in hyperbolic geometry and relativistic physics

Gyrogroup theory and its applications is introduced and explored, exposing the fascinating interplay between Thomas precession of special relativity theory and hyperbolic geometry. The abstract Thomas precession, called Thomas gyration, gives rise to grouplike objects called gyrogroups [A, A. Ungar, Am. J. Phys.59, 824 (1991)] the underlying axions of which are presented. The prefix gyro extensively used in terms like gyrogroups, gyroassociative and gyrocommutative laws, gyroautomorphisms, and gyrosemidirect products, stems from their underlying abstract Thomas gyration. Thomas gyration is tailor made for hyperbolic geometry. In a similar way that commutative groups underlie vector spaces, gyrocommutative gyrogroups underlie gyrovector spaces. Gyrovector spaces, in turn, provide a most natural setting for hyperbolic geometry in full analogy with vector spaces that provide the setting for Euclidean geometry. As such, their applicability to relativistic physics and its spacetime geometry is obvious.     

Clay‐induced Preferred Orientation in Polyethylene/Compatibilized Clay Nanocomposites

Nanocomposites of the organically modified clay Cloisite^® 15A (CL15A) dispersed in HDPE‐g‐MA were prepared by melt‐compounding. Microcomposites of the same clay with HDPE were also obtained with similar procedures. The spherulitic morphology of the polymer matrix was evidenced by optical microscopy in thin films, whereas the structure of the up to 2‐mm–thick, compression‐molded samples was investigated by WAXD and SAXS. Preferred orientation of both the clay and the HDPE crystallites were evidenced in the microcomposites and, to a greater extent, in nanocomposites, whereas in HDPE and HDPE‐g‐MA control specimens hardly any anisotropy was detected. The degree of orientation of PE crystals increases with CL15A concentration, but also with clay exfoliation, with lower cooling rates and decreasing sample thickness. The orientation of the clay platelets parallel to the compression‐molded surface appears to be determined by the platelets anisotropy and by shear in the mixing and the compression‐molding procedures. In turn, it determines the preferred uniaxial orientation of HDPE crystals, which have their crystallographic a axis orthogonal, while b and c are coplanar, to the sample surface, as already reported in the literature for melt‐crystallized HDPE films with thickness below 0.3 μm. It is proposed that the HDPE orientation results from confined crystallization between parallel clay platelets which are on average less than 0.1 μm apart. Simple models, qualitatively accounting for the observed orientation of HDPE, are discussed. Organized architectures resulting from confined crystallization of the polymer matrix in nanocomposites with appropriate anisotropic fillers may be a general feature, important in determining key properties of these systems.