Persistent states in vision break universality and time invariance

Studies of perception usually emphasize processes that are largely universal across observers and—except for short-term fluctuations—stationary over time. Here we test the universality and stationarity assumptions with two families of ambiguous visual stimuli. Each stimulus can be perceived in two different ways, parameterized by two opposite directions from a continuous circular variable. A large-sample study showed that almost all observers have preferred directions or biases, with directions lying within 90 degrees of the bias direction nearly always perceived and opposite directions almost never perceived. The biases differ dramatically from one observer to the next, and although nearly every bias direction occurs in the population, the population distributions of the biases are nonuniform, featuring asymmetric peaks in the cardinal directions. The biases for the two families of stimuli are independent and have distinct population distributions. Following external perturbations and spontaneous fluctuations, the biases decay over tens of seconds toward their initial values. Persistent changes in the biases are found on time scales of several minutes to 1 hour. On scales of days to months, the biases undergo a variety of dynamical processes such as drifts, jumps, and oscillations. The global statistics of a majority of these long-term time series are well modeled as random walk processes. The measurable fluctuations of these hitherto unknown degrees of freedom show that the assumptions of universality and stationarity in perception may be unwarranted and that models of perception must include both directly observable variables as well as covert, persistent states.The neural networks underlying visual perception are complex systems and, as such, undoubtedly have internal states. The formal notion of “state” can be defined as the minimal set of variables that, together with the input to a system and the fixed processing mechanisms, allows one to predict the system’s output (1). If perception is a function of both the sensory input and internal states, then—because states can vary both across individual observers and over time—the presence of an internal state would manifest itself as potentially large individual differences in the perception of the same stimulus and in coherent temporal variations of perception of the same stimulus over time in a single observer. It is known that visual functions can be modulated (2) on brief time scales by priming (3–6), aftereffects (7–9), and sequence effects (10–13) [and sometimes on larger time scales as well (14)]; can undergo visible short-term fluctuations in the presence of multistable stimuli (15–20); and can undergo long-term or permanent changes in their structure through learning (21–24). Despite these examples, little is known about internal states of the visual system. In terms of underlying mechanisms, the internal state is represented naturally in recurrent but not in feed-forward neural networks (25, 26).Here we measure patterns of biases in two families of visual stimuli and show that, contrary to most known cases, these patterns can vary radically from one observer to the next, leading to stimuli that are often perceived in opposite ways by different observers. We show that these bias patterns can be predicted to a large extent by simple variables. We therefore call these parameters “state variables.” They constitute a form of long-term but dynamic memory in perception and are related to but distinct from the phenomenon of short-term coherence in the perception of multistable stimuli known as sensory memory (15–20), as we discuss below.The stimuli in the first family, which we call structure–from–motion (SFM), consist of moving dots simulating planes rotating in depth (Fig. 1A). [Examples of stimuli and response procedures for the two families of stimuli may be seen at lab-perception.org/demo/p/sfm and lab-perception.org/demo/p/tfm. Following the 16-trial session, the web page displays the participant’s bias.] Each stimulus can be perceived as having one of two tilts (27–29), separated by 180 degrees (Fig. 1 B and I). The stimuli in the second family, transparency–from–motion (TFM), consist of two sets of dots moving in opposite directions (Fig. 1C). The two sets of dots are usually perceived as transparent layers, one of which is seen as being closer or more salient (30–32), also giving rise to a 180 degree ambiguity (Fig. 1D). Observers reported which of the two tilts they perceived for SFM stimuli and which of the two motion directions they perceived closer for TFM stimuli. Successive stimuli had different orientations (tilts or motion directions), sampled in random order from the entire 360 degree range—in contrast to procedures used to study spontaneous fluctuations (15–20), in which only one stimulus is presented. To reduce spontaneous fluctuations, stimuli were brief (0.5 s).Open in a separate windowFig. 1.The two families of ambiguous stimuli and summary of data analysis. (A and B) SFM stimuli. Optic flow such as in A is ambiguous because it can be generated by the two configurations shown in B, corresponding to surfaces with tilts that differ by 180 degrees (see I for definition) and opposite directions of rotation. (Stimuli used in the study had 45 degrees between tilts and rotation axes, rather than 0 degrees, as shown here.) (C and D) TFM stimuli. Two sets of dots moving in opposite directions (C), with no explicit depth cues, are usually perceived as segregated by motion direction into two transparent layers, with one of the layers seen as closer or more salient than the other; (D) the motion direction of the front or salient layer is ambiguous by 180 degrees. (E) We represent one stimulus by two opposite-facing arrows, corresponding to the two possible tilts (SFM, shown here) or front-layer motion directions (TFM) that can be perceived. We will represent the tilt or motion direction that was reported by the darker arrow. (F) A typical pattern of responses obtained when we present a series of tilts or motion directions. Actual experiments had more values of tilts or directions. (G) To calculate the bias vector, we take the sum of the unit vectors corresponding to the perceived tilts or motion directions. (H) The direction of the bias vector yields the preferred tilt or motion direction, whereas its length (normalized by its maximum value) is a measure of bias strength. (I) Illustration of slant and tilt, the variables we use to parametrize surface orientations in SFM stimuli. Tilt is the orientation in the image plane of the projection of the surface normal vector.Each twofold ambiguity at a different stimulus orientation could have been resolved as an independent stochastic decision, which would have yielded an isotropic pattern of perceptual decisions across stimulus orientations. As we shall show, however, perceptions at different orientations are far from isotropic, following a pattern that is both highly stereotypical and idiosyncratic. The individual differences are governed by state variables—bias parameters that exhibit coherence over time, while also undergoing cumulative changes—whose dynamics we explore below.     

Trade-off between curvature tuning and position invariance in visual area V4

Humans can rapidly recognize a multitude of objects despite differences in their appearance. The neural mechanisms that endow high-level sensory neurons with both selectivity to complex stimulus features and “tolerance” or invariance to identity-preserving transformations, such as spatial translation, remain poorly understood. Previous studies have demonstrated that both tolerance and selectivity to conjunctions of features are increased at successive stages of the ventral visual stream that mediates visual recognition. Within a given area, such as visual area V4 or the inferotemporal cortex, tolerance has been found to be inversely related to the sparseness of neural responses, which in turn was positively correlated with conjunction selectivity. However, the direct relationship between tolerance and conjunction selectivity has been difficult to establish, with different studies reporting either an inverse or no significant relationship. To resolve this, we measured V4 responses to natural scenes, and using recently developed statistical techniques, we estimated both the relevant stimulus features and the range of translation invariance for each neuron. Focusing the analysis on tuning to curvature, a tractable example of conjunction selectivity, we found that neurons that were tuned to more curved contours had smaller ranges of position invariance and produced sparser responses to natural stimuli. These trade-offs provide empirical support for recent theories of how the visual system estimates 3D shapes from shading and texture flows, as well as the tiling hypothesis of the visual space for different curvature values.     

Hierarchical random walks in trace fossils and the origin of optimal search behavior

Efficient searching is crucial for timely location of food and other resources. Recent studies show that diverse living animals use a theoretically optimal scale-free random search for sparse resources known as a Lévy walk, but little is known of the origins and evolution of foraging behavior and the search strategies of extinct organisms. Here, using simulations of self-avoiding trace fossil trails, we show that randomly introduced strophotaxis (U-turns)—initiated by obstructions such as self-trail avoidance or innate cueing—leads to random looping patterns with clustering across increasing scales that is consistent with the presence of Lévy walks. This predicts that optimal Lévy searches may emerge from simple behaviors observed in fossil trails. We then analyzed fossilized trails of benthic marine organisms by using a novel path analysis technique and find the first evidence, to our knowledge, of Lévy-like search strategies in extinct animals. Our results show that simple search behaviors of extinct animals in heterogeneous environments give rise to hierarchically nested Brownian walk clusters that converge to optimal Lévy patterns. Primary productivity collapse and large-scale food scarcity characterizing mass extinctions evident in the fossil record may have triggered adaptation of optimal Lévy-like searches. The findings suggest that Lévy-like behavior has been used by foragers since at least the Eocene but may have a more ancient origin, which might explain recent widespread observations of such patterns among modern taxa.The specific pattern of searching movements used by an organism to locate food relative to the food’s distribution closely determines the number of successful encounters (1–3). The evolution of optimal search patterns is predicted because natural selection favors individuals that are best able to find resources critical to survival (4). It is recognized, however, that the natural environment is too complex for evolution to produce a behavior pattern that is optimal across all scales and contexts (5). Rather, simple rules probably will evolve that, on average, perform well in their natural environment (5). Such rules are exemplified in the different movement modes that tend to characterize behavior across different spatiotemporal scales. For instance, simple deterministic foraging searches, such as Archimedean spirals (6) or area-restricted searching (7), that are driven by sensory and cognitive abilities are efficient where food distributions are known, easily detected, or predictable. However, these patterns are inefficient when food resources are sparsely or patchily distributed and the forager has incomplete information on resource location; under these conditions, probabilistic searches such as Lévy walks become advantageous (1–3).Theory predicts that Lévy walk search strategies should be optimal where food is sparse and distributed unpredictably (1), whereas Brownian walks are sufficiently efficient for locating abundant prey (2). A Lévy walk search pattern comprises displacements (move steps) drawn from a probability distribution with a heavy power-law tail that results in a fractal pattern of “walk clusters” with no characteristic scale, such that P(l) ∼ l^−µ, with 1 < µ ≤ 3, where l is the move step length between turns and µ the power-law exponent. Over many iterations, a Lévy walk will be distributed much further from its starting position than a Brownian walk of the same length [hence is termed superdiffusive (8)], because small-step walk clusters are interspersed by long “steps” to new locations, with this pattern repeating across all scales. It has been demonstrated that a Lévy walk with exponent µ ∼2 is optimal when the search targets are not depleted or rejected once visited but instead may be revisited profitably, either because they replenish overtime or because targets are distributed patchily (1, 2). Importantly, Lévy searches with µ ∼2 are optimal for a very broad range of target densities and distributions (9). In the very low-density regime, Lévy strategies remain the optimal solution with the optimal exponent 1 < µ_opt ≤ 2 dependent on specific environmental properties, such as the degree of spatial landscape heterogeneity or temporal target revisitability (10, 11). Consequently, optimal Lévy searches result in more predictable target encounters during foraging in otherwise unpredictable environments (9). Because Lévy walks can optimize search efficiencies in this way, it is proposed that natural selection should have led to adaptations for Lévy walk foraging [the Lévy flight foraging (LFF) hypothesis] (1–3). The apparent ubiquity of Lévy patterns among extant organisms, including humans (1–3, 12–18), suggests that searches that approximate them have evolved naturally (3). It has been hypothesized that behavioral adaptations to changes in environmental resources cue the switching between localized Brownian and Lévy random searching (2, 3, 13) or that sensory interactions with heterogeneous environments may give rise to Lévy movement patterns (an emergent phenomena) (19); however, the origins of such potential mechanisms remain elusive.The fossilized records of animal movements preserved as trails and burrows (trace fossils) are the only direct record of extinct organisms’ behavior and may provide a means to understand the evolution of search strategies in ancient landscapes, including during dramatic environmental changes (6, 20, 21). At intervals throughout evolutionary history, organisms have faced large-scale collapses of primary productivity due to abiotic environmental changes, such as volcanism and global warming, that often are associated with mass extinctions of species (22, 23). This raises the possibility that random search patterns such as Lévy walks, with characteristic long steps to new locations, might have acted to increase the likelihood of ancient organisms finding scarce resources, as the search time to find distant patches is minimized in this movement strategy compared with Brownian motion (2). Nevertheless, so far, only localized foraging patterns based on simple taxes have been identified in trace fossils (6, 20, 21).An early computer simulation (20) showed that the patterns recorded by many trace fossils could be reconstructed in model foragers by using three simple “rules”: “phobotaxis,” which forbids an individual from crossing its own trail; “thigmotaxis,” which compels an individual to stay close to an existing trail; and “strophotaxis,” which is the propensity for making U-turns and which may be cued innately or triggered by the presence of an obstruction or other discontinuity. These three basic patterns of behavior now underlie most theories of spiral and meandering trace fossils (24). A general characteristic of many fossil trails is that they resemble self-avoiding random walks, as there is minimal recrossing of existing tracks (24). This resemblance is more than superficial, because some trace fossils from deep-water turbidite fan settings are fractal (25, 26), and have fractal dimensions typically estimated to be between 1.5 and 1.6 (25), which span the fractal dimension (1.55) of a self-avoiding random walk. This suggests that trace fossils also may be modeled as Lévy walks, because they share with self-avoiding random walks the same range of fractal dimensions and so exhibit, on average, the same number of subclusters per cluster with change of scale (27). However, to our knowledge, no previous study investigated the possibility of Lévy behavior occurring in ancient organisms.     

Local statistics in natural scenes predict the saliency of synthetic textures

The visual system is challenged with extracting and representing behaviorally relevant information contained in natural inputs of great complexity and detail. This task begins in the sensory periphery: retinal receptive fields and circuits are matched to the first and second-order statistical structure of natural inputs. This matching enables the retina to remove stimulus components that are predictable (and therefore uninformative), and primarily transmit what is unpredictable (and therefore informative). Here we show that this design principle applies to more complex aspects of natural scenes, and to central visual processing. We do this by classifying high-order statistics of natural scenes according to whether they are uninformative vs. informative. We find that the uninformative ones are perceptually nonsalient, while the informative ones are highly salient, and correspond to previously identified perceptual mechanisms whose neural basis is likely central. Our results suggest that the principle of efficient coding not only accounts for filtering operations in the sensory periphery, but also shapes subsequent stages of sensory processing that are sensitive to high-order image statistics.     

Evidence for the extraterrestrial origin of a natural quasicrystal

We present evidence that a rock sample found in the Koryak Mountains in Russia and containing icosahedrite, an icosahedral quasicrystalline phase with composition Al(63)Cu(24)Fe(13), is part of a meteorite, likely formed in the early solar system about 4.5 Gya. The quasicrystal grains are intergrown with diopside, forsterite, stishovite, and additional metallic phases [khatyrkite (CuAl(2)), cupalite (CuAl), and β-phase (AlCuFe)]. This assemblage, in turn, is enclosed in a white rind consisting of diopside, hedenbergite, spinel (MgAl(2)O(4)), nepheline, and forsterite. Particularly notable is a grain of stishovite (from the interior), a tetragonal polymorph of silica that only occurs at ultrahigh pressures (≥ 10 Gpa), that contains an inclusion of quasicrystal. An extraterrestrial origin is inferred from secondary ion mass spectrometry (18)O/(16)O and (17)O/(16)O measurements of the pyroxene and olivine intergrown with the metal that show them to have isotopic compositions unlike any terrestrial minerals and instead overlap those of anhydrous phases in carbonaceous chondrite meteorites. The spinel from the white rind has an isotopic composition suggesting that it was part of a calcium-aluminum-rich inclusion similar to those found in CV3 chondrites. The mechanism that produced this exotic assemblage is not yet understood. The assemblage (metallic copper-aluminum alloy) is extremely reduced, and the close association of aluminum (high temperature refractory lithophile) with copper (low temperature chalcophile) is unexpected. Nevertheless, our evidence indicates that quasicrystals can form naturally under astrophysical conditions and remain stable over cosmic timescales, giving unique insights on their existence in nature and stability.     

A Basic Study on the Eye Fixation Points in Endoscopic Observation with Special Reference to the Difference Between the Beginners and Experts

Accurate image analysis is essential for correct diagnosis in gastrointestinal endoscopy. In the past, the process of diagnosis has varied based merely on the personal experience of the examiner, and yet there has been no basic study concerning its improvement. We conducted a basic study on endoscopic image analysis particularly with regard to eye fixation points, and noticed that there was a significant difference between beginners and experts. The beginners tended to fix their eyes on the area showing a larger color tone difference, whereas the experts tended to have their fixation points on areas with less of a color tone difference     

Lack of exercise leads to significant and reversible loss of scale invariance in both aged and young mice

In healthy humans and other animals, behavioral activity exhibits scale invariance over multiple timescales from minutes to 24 h, whereas in aging or diseased conditions, scale invariance is usually reduced significantly. Accordingly, scale invariance can be a potential marker for health. Given compelling indications that exercise is beneficial for mental and physical health, we tested to what extent a lack of exercise affects scale invariance in young and aged animals. We studied six or more mice in each of four age groups (0.5, 1, 1.5, and 2 y) and observed an age-related deterioration of scale invariance in activity fluctuations. We found that limiting the amount of exercise, by removing the running wheels, leads to loss of scale-invariant properties in all age groups. Remarkably, in both young and old animals a lack of exercise reduced the scale invariance in activity fluctuations to the same level. We next showed that scale invariance can be restored by returning the running wheels. Exercise during the active period also improved scale invariance during the resting period, suggesting that activity during the active phase may also be beneficial for the resting phase. Finally, our data showed that exercise had a stronger influence on scale invariance than the effect of age. The data suggest that exercise is beneficial as revealed by scale-invariant parameters and that, even in young animals, a lack of exercise leads to strong deterioration in these parameters.Many physiologic variables, such as heart rate, respiration, and locomotor activity, display scale-invariant or “fractal” properties, characterized by temporal structures that are similar across different timescales (1–6). Fractal patterns in physiological systems are intrinsic characteristics that are independent of external stimuli (7–9). The presence of fractal patterns is associated with health advantages, such as system integrity, as well as adaptability, and physiologic systems lose their scale invariance under diseased or aging conditions. The scale invariance in, for example, heart rate is reduced in congestive heart failure patients, and moreover, changes in fractal patterns have been demonstrated to be better predictors of morbidity and mortality than classical biomarkers (2, 3, 10).Detrended fluctuation analysis (DFA) is a widely used method to quantify correlations in nonstationary physiological time series, such as heart rate and gait (1–3, 11, 12). The DFA provides information on the amplitude of the fluctuations at different timescales. The correlation in the fluctuations is described by the scaling exponent α. A value of α close to 1.0 indicates a delicate balance between uncorrelated randomness (α = 0.5) and regularity (α = 1.5), and is observed in healthy physiological systems (1). Under pathological conditions such as Huntington’s disease and Alzheimer’s disease, the physiological fluctuations are measurably different from 1 and are either too random or too regular (11, 12).Locomotor activity in both humans and rodents displays scale-invariant fluctuations for timescales of seconds up to ∼24 h (8, 12, 13). The mechanism for generating scale-invariant activity patterns is not understood. Recent studies showed that scale-invariant activity patterns are disrupted with aging and in patients suffering from dementia (12). The degree of the disruption is strongly correlated with the circadian neurotransmitter content in the suprachiasmatic nucleus (SCN) (14), the master clock in mammals that regulates circadian rhythms in physiology and behavior (15).In the past few years, it has become increasingly clear that exercise is beneficial for the circadian system (16–18). Furthermore, exercise improves the immune system, helps to prevent obesity, cardiovascular disease, and type 2 diabetes mellitus, and improves memory (19–23). The World Health Organization has pinpointed a lack of exercise as a major risk factor for diseases, including metabolic, cardiovascular, and immune diseases (24, 25). The aim of the present study is to determine whether a lack of exercise affects age-related deterioration in scale invariance of locomotor activity and whether, in turn, enhanced activity levels can lead to improvement. We found that, unexpectedly, a lack of exercise leads to loss of scale invariance not only in aged but also in young animals. Following a period of inactivity, exercise resulted in complete restoration of scale invariance in young animals and substantial improvement in old animals.     

Phase separation in solutions of monoclonal antibodies and the effect of human serum albumin

We report the observation of liquid-liquid phase separation in a solution of human monoclonal antibody, IgG2, and the effects of human serum albumin, a major blood protein, on this phase separation. We find a significant reduction of phase separation temperature in the presence of albumin, and a preferential partitioning of the albumin into the antibody-rich phase. We provide a general thermodynamic analysis of the antibody-albumin mixture phase diagram and relate its features to the magnitude of the effective interprotein interactions. Our analysis suggests that additives (HSA in this report), which have moderate attraction with antibody molecules, may be used to forestall undesirable protein condensation in antibody solutions. Our findings are relevant to understanding the stability of pharmaceutical solutions of antibodies and the mechanisms of cryoglobulinemia.     

Classification images reveal decision variables and strategies in forced choice tasks

Despite decades of research, there is still uncertainty about how people make simple decisions about perceptual stimuli. Most theories assume that perceptual decisions are based on decision variables, which are internal variables that encode task-relevant information. However, decision variables are usually considered to be theoretical constructs that cannot be measured directly, and this often makes it difficult to test theories of perceptual decision making. Here we show how to measure decision variables on individual trials, and we use these measurements to test theories of perceptual decision making more directly than has previously been possible. We measure classification images, which are estimates of templates that observers use to extract information from stimuli. We then calculate the dot product of these classification images with the stimuli to estimate observers'' decision variables. Finally, we reconstruct each observer''s “decision space,” a map that shows the probability of the observer’s responses for all values of the decision variables. We use this method to examine decision strategies in two-alternative forced choice (2AFC) tasks, for which there are several competing models. In one experiment, the resulting decision spaces support the difference model, a classic theory of 2AFC decisions. In a second experiment, we find unexpected decision spaces that are not predicted by standard models of 2AFC decisions, and that suggest intrinsic uncertainty or soft thresholding. These experiments give new evidence regarding observers’ strategies in 2AFC tasks, and they show how measuring decision variables can answer long-standing questions about perceptual decision making.Many current questions about human cognition are related to how people make decisions, including decisions based on perceptual information. For example, how do we decide whether a search target is present in a cluttered display? How do we decide when to respond in a task where both speed and accuracy are important? How do we judge which of two signals is present in a discrimination task?Most theories of perceptual decision making rely on the notion of a decision variable, a quantity that the observer calculates from the stimulus to summarize task-relevant information, e.g., the probability that a faint signal is present in a detection task (1). Some theories of decision making are very simple, e.g., the observer gives one response if the decision variable is greater than a fixed criterion, and another response if the decision variable is less than the criterion. Other theories use more complex decision rules. Testing theories of decision making would be much easier if we had access to observers’ decision variables, but these are usually thought of as theoretical constructs that cannot be measured psychophysically. Here we show that in some tasks, it is possible to estimate decision variables on individual trials, and this provides a very direct way of testing theories of perceptual decision making. We use this method to examine the long-standing question of how people make decisions in two-alternative forced choice (2AFC) tasks.     

Factorial invariance issues in the study of adult personality: an example using Levenson's locus of control scale.

Confirmatory factor analysis was used to examine factorial invariance across young, middle-aged, and elderly age groups, using Levenson's multidimensional locus of control (LoC) scale, which measures beliefs in Internal Control (I), Control by Powerful Others (P), and Chinese (C). Data were obtained from 563 individuals ranging in age from 25 years to 75 years of age who resided in Southeastern Louisiana. Results indicated that Levenson's 3-factor conceptualization of control was not a valid representation of the samples' responses. A model that specified the elimination of 17 unreliable items and the formation of both an internal and an external control factor that was based on the seven remaining I and P items provided an adequate fit to the data for the three age groups, though when additional constraints were specified, factorial invariance was not demonstrated. The 7-item I and P factor model generated a pattern of relationships with other measures which was similar to the pattern found if all items of the I and P scales were used.     

Retina is structured to process an excess of darkness in natural scenes

Retinal ganglion cells that respond selectively to a dark spot on a brighter background (OFF cells) have smaller dendritic fields than their ON counterparts and are more numerous. OFF cells also branch more densely, and thus collect more synapses per visual angle. That the retina devotes more resources to processing dark contrasts predicts that natural images contain more dark information. We confirm this across a range of spatial scales and trace the origin of this phenomenon to the statistical structure of natural scenes. We show that the optimal mosaics for encoding natural images are also asymmetric, with OFF elements smaller and more numerous, matching retinal structure. Finally, the concentration of synapses within a dendritic field matches the information content, suggesting a simple principle to connect a concrete fact of neuroanatomy with the abstract concept of information: equal synapses for equal bits.     

HBsAg-positive Swedish blood donors: natural history and origin of infection

99 HBsAg-positive blood donors (BDs) were discovered in G?teborg during 1970-84. Of the 82 patients where the outcome is known 46 had transient and 36 persistent antigenemia. Chronic hepatitis was found in 6 patients while 30 were asymptomatic carriers. Three BDs had died, 1 of them from cholangiocellular cancer. An obvious mode of transmission was demonstrated for 19 BDs, i.v. drug abuse being the most frequent one. Five BDs originated from countries with a known high prevalence of hepatitis B virus (HBV). Family contacts of the remaining carriers had serological markers for HBV in the following frequencies: mothers 46%, siblings 39%, fathers 25%, children 13%, spouses 10%. Only children of female carriers had markers for HBV infection. Intrafamiliar transmission during childhood is an important route of transmission even in a country with low HBV endemicity and amongst people without connection with endemic regions. This population may be susceptible to the consequences of a long-term carriership of HBV.     

A rodent model for the study of invariant visual object recognition

The human visual system is able to recognize objects despite tremendous variation in their appearance on the retina resulting from variation in view, size, lighting, etc. This ability—known as “invariant” object recognition—is central to visual perception, yet its computational underpinnings are poorly understood. Traditionally, nonhuman primates have been the animal model-of-choice for investigating the neuronal substrates of invariant recognition, because their visual systems closely mirror our own. Meanwhile, simpler and more accessible animal models such as rodents have been largely overlooked as possible models of higher-level visual functions, because their brains are often assumed to lack advanced visual processing machinery. As a result, little is known about rodents'' ability to process complex visual stimuli in the face of real-world image variation. In the present work, we show that rats possess more advanced visual abilities than previously appreciated. Specifically, we trained pigmented rats to perform a visual task that required them to recognize objects despite substantial variation in their appearance, due to changes in size, view, and lighting. Critically, rats were able to spontaneously generalize to previously unseen transformations of learned objects. These results provide the first systematic evidence for invariant object recognition in rats and argue for an increased focus on rodents as models for studying high-level visual processing.     

The activities of daily vision scale: a useful tool to assess fall risk in older adults with vision impairment

OBJECTIVE: To evaluate the validity of the Activities of Daily Vision Scale (ADVS) as a tool to assess fall risk in older adults with vision impairment. DESIGN: Cross-sectional assessments of visual function and retrospective collection of fall data. SETTING: The outpatient medical clinics of an academic tertiary care community hospital. PARTICIPANTS: Randomly selected sample (n = 143) of older (> or = 65 years) patients seen at the outpatient medical clinics at Nassau County Medical Center in Long Island, New York. These patients had one or more of five ocular conditions: refractive errors (n = 90), cataracts (n = 77), glaucoma (n = 29), diabetic retinopathy (n = 19), and/or macular degeneration (n = 6). MEASUREMENTS: Visual function, assessed using the ADVS, demonstrated scores ranging from 0 (marked visual disability) to 100 (no visual difficulty). Fall history and the presence of eye disease were based on the self-recall of patients. Fall history was assessed retrospectively over a 1-year period from the time of the interview. RESULTS: Thirteen percent of the subjects reported having one or more falls during the 1-year period before the time of the interview. These subjects scored significantly lower on the ADVS compared with the scores of the group that did not report falls (74 +/- 22 vs 85 +/- 14, P < .01). Using a cutoff score of 90 points (10% loss of visual function on the ADVS), the ADVS had a 67% sensitivity in identifying those patients who had falls. Among the patients with glaucoma and those with diabetic retinopathy, the ADVS had a 100% sensitivity in identifying those patients who reported a history of falls. In patients with cataracts and refractive errors, the ADVS had a sensitivity of 82% and 64%, respectively, in identifying patients with a history of falls. The number of falls reported by the subjects showed no relationship with the ADVS scores. CONCLUSION: The results from this study suggest that the ADVS may prove to be a useful tool to assess fall risk in older adults with vision impairment, especially in those persons with glaucoma, diabetic retinopathy, and/or cataracts.     

A model for the origin of biological catalysis.

We propose a mathematical model for the next stage in the origin of life after that treated in our earlier work. At this stage we introduce the possibility of the modification of the environment by the information-containing entities and feedback between the environment and the population of macromolecules and hence provide a model for the development of the Eigen hypercycle.     

Self-organization, the cascade model, and natural hazards

We consider the frequency-size statistics of two natural hazards, forest fires and landslides. Both appear to satisfy power-law (fractal) distributions to a good approximation under a wide variety of conditions. Two simple cellular-automata models have been proposed as analogs for this observed behavior, the forest fire model for forest fires and the sand pile model for landslides. The behavior of these models can be understood in terms of a self-similar inverse cascade. For the forest fire model the cascade consists of the coalescence of clusters of trees; for the sand pile model the cascade consists of the coalescence of metastable regions.     

Non-invasive assessment of pulse wave velocity in mice by means of ultrasound images

Objective

Pulse wave velocity (PWV) is considered as a surrogate marker of arterial stiffness and could be useful for characterizing cardiovascular disease progression even in mouse models. Aim of this study was to develop an image process algorithm for assessing arterial PWV in mice using ultrasound images only and test it on the evaluation of age-associated differences in abdominal aorta PWV.

Methods

Ultrasound scans were obtained from ten adult (mean age: 5.5 months) and nine old (mean age: 15.5 months) wild type male mice (strain C57BL6) under gaseous anesthesia. For each mouse, instantaneous values of diameter and flow velocity were obtained from abdominal aorta B-mode and PW-Doppler, respectively. Single-beat mean diameter and velocity were calculated providing the velocity-diameter (lnD-V) loop. PWV values for both the early systolic phase (aaPWV) and the late systolic one (aaPWV_ls) were obtained from the slope of the corresponding linear parts of the loop. Relative distension (relD) was calculated from the mean diameter signal.

Results

aaPWV values for adult mice (1.91 ± 0.44 m/s) were significantly lower (p < 0.01) than those obtained for older ones (2.71 ± 0.63 m/s) and the same result was found for aaPWV_ls (2.68 ± 0.68 vs 3.67 ± 0.95 m/s; p < 0.05). relD measurements were significantly higher (p < 0.01) in adult (22.7% ± 5.2%) compared with older animal evaluations (15.8% ± 3.9%).

Conclusions

The proposed system discriminates well between age groups and supplies a non-invasive evaluation of anatomical and functional parameters of the mouse abdominal aorta. Since it provides a non-invasive PWV assessment from ultrasound (US) images only, it may offer a simple and useful system for evaluation of local vascular stiffness at other arterial site in the mouse, such as the carotid artery.     

Maximizing power in seroepidemiological studies through the use of the proportional odds model

Epidemiological studies of zoonotic influenza and other infectious diseases often rely upon analysis of levels of antibody titer. In most of these studies, the antibody titer data are dichotomized based on a chosen cut-point and analyzed with a traditional binary logistic regression. However, cut-points are often arbitrary, particularly those selected for rare diseases or for infections for which serologic assays are imperfect. Alternatively,the data can be left in the original form, as ordinal levels of antibody titer, and analyzed using the proportional odds model. We show why this approach yields superior power to detect risk factors. Additionally, we illustrate the advantages of using the proportional odds model with the analyses of zoonotic influenza antibody titer data.     

Transvaginal natural orifice transluminal endoscopic surgery in the diagnosis of ascites of unknown origin

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