The statistics of local motion signals in naturalistic movies

Extraction of motion from visual input plays an important role in many visual tasks, such as separation of figure from ground and navigation through space. Several kinds of local motion signals have been distinguished based on mathematical and computational considerations (e.g., motion based on spatiotemporal correlation of luminance, and motion based on spatiotemporal correlation of flicker), but little is known about the prevalence of these different kinds of signals in the real world. To address this question, we first note that different kinds of local motion signals (e.g., Fourier, non-Fourier, and glider) are characterized by second-and higher-order correlations in slanted spatiotemporal regions. The prevalence of local motion signals in natural scenes can thus be estimated by measuring the extent to which each of these correlations are present in space-time patches and whether they are coherent across spatiotemporal scales. We apply this technique to several popular movies. The results show that all three kinds of local motion signals are present in natural movies. While the balance of the different kinds of motion signals varies from segment to segment during the course of each movie, the overall pattern of prevalence of the different kinds of motion and their subtypes, and the correlations between them, is strikingly similar across movies (but is absent from white noise movies). In sum, naturalistic movies contain a diversity of local motion signals that occur with a consistent prevalence and pattern of covariation, indicating a substantial regularity of their high-order spatiotemporal image statistics

Ogre-Faced, Net-Casting Spiders Use Auditory Cues to Detect Airborne Prey

Prey-capture behavior among spiders varies greatly from passive entrapment in webs to running down prey items on foot. Somewhere in the middle are the ogre-faced, net-casting spiders (Deinopidae: Deinopis) that actively capture prey while being suspended within a frame web. Using a net held between their front four legs, these spiders lunge downward to ensnare prey from off the ground beneath them. This “forward strike” is sensorially mediated by a massive pair of hypersensitive, night-vision eyes. Deinopids can also intercept flying insects with a “backward strike,” a ballistically rapid, overhead back-twist, that seems not to rely on visual cues. Past reports have hypothesized a role of acoustic detection in backward strike behavior. Here, we report that the net-casting spider, Deinopis spinosa, can detect auditory stimuli from at least 2 m from the sound source, at or above 60 dB SPL, and that this acoustic sensitivity is sufficient to trigger backward strike behavior. We present neurophysiological recordings in response to acoustic stimulation, both from sound-sensitive areas in the brain and isolated forelegs, which demonstrate a broad range of auditory sensitivity (100–10,000 Hz). Moreover, we conducted behavioral assays of acoustic stimulation that confirm acoustic triggering of backward net-casting by frequencies in harmony with flight tones of known prey. However, acoustic stimulation using higher frequency sounds did not elicit predatory responses in D. spinosa. We hypothesize higher frequencies are emitted by avian predators and that detecting these auditory cues may aid in antipredator behavior

Low root-to-root transmission of a tobamovirus, yellow tailflower mild mottle virus, and resilience of its virions

Tobamoviruses are serious pathogens because they have extremely stable virions, they are transmitted by contact, and they often induce severe disease in crops. Knowledge of the routes of transmission and resilience of tobamovirus virions is essential in understanding the epidemiology of this group of viruses. We used an isolate of the tobamovirus yellow tailflower mild mottle virus (YTMMV) to examine root-to-root transmission in soil and in a hydroponic growth environment. Root-to-root transmission occurred rarely, and when it occurred plants did not exhibit systemic movement of the virus from the roots to the shoots over a 30-day period. The resilience of YTMMV virions was tested in dried leaf tissue over time periods from one hour to one year under temperatures ranging from -80°C to 160°C. Infectivity was maintained for at least a year when incubated at -80°C, 22°C or at fluctuating ambient temperatures of 0.8°C to 44.4°C, but incubation under dry conditions at 160°C for >4 days eliminated infectivity. Exposure of virions to 0.1 M sodium hydroxide or 20% w/v skim milk solution for 30 min, treatments recommended for tobamovirus inactivation, did not abolish infectivity of YTMMV

Local Motion Signals - Prevalence, Responses And Interactions

Extraction of local motion signals is crucial for our survival. Lack of information from local motion signals will significantly reduce our ability to discriminate objects from background, avoid obstacles, and navigate. Despite the apparent effortlessness with which we perceive visual motion, there are indications that the underlying neural computations are complex. Three kinds of local motion signals have been distinguished, based on the kinds of spatiotemporal correlations that generate them: Fourier (F), based on 2-point correlations [1]; non-Fourier (NF), based on 4-point correlations [2]; and glider (G), based on 3-point correlations [3]. G signals have two subtypes, expansion and contraction, associated with objects that are looming and receding, respectively. Detection of isolated G and NF signals cannot be mediated by a purely multiplicative cross-correlator or a purely quadratic motion energy model. G signals have recently attracted substantial attention, following the demonstration that a wide range of species (human [3], macaque [4, 5], zebrafish [6], dragonfly [5], and fruitfly [7]) respond to them in similar ways suggesting that there are advantages to using these signals in visual tasks. This work expands the above lines of research in several respects. First, our computational work shows that these motion signals appear in natural scenes and characterizes the basic statistical relationships between them [8]. Second, we report neurophysiological recordings in two distinct visual-speciaist species (macaques and dragonflies) that demonstrate that at the neuronal level, cells response in a similar manner to motion signals in many respects, although there are subtle differences in responses between the species. This convergence at the algorithmic and neural-implementation levels indicate the fundamental biological importance of using the many kinds of motion signals to guide behavior. Finally, we carried out a psychophysical experiment to probe human ability to use multiple kinds of local motion signals simultaneously to solve simple directional task. We found that humans can combine different kinds of motion signals to solve this task, and, interestingly, that sensitivity to different kinds of motion signals is context-dependent

The statistics of local motion signals in naturalistic movies

Extraction of motion from visual input plays an important role in many visual tasks, such as separation of figure from ground and navigation through space. Several kinds of local motion signals have been distinguished based on mathematical and computational considerations (e.g., motion based on spatiotemporal correlation of luminance, and motion based on spatiotemporal correlation of flicker), but little is known about the prevalence of these different kinds of signals in the real world. To address this question, we first note that different kinds of local motion signals (e.g., Fourier, non-Fourier, and glider) are characterized by second-and higher-order correlations in slanted spatiotemporal regions. The prevalence of local motion signals in natural scenes can thus be estimated by measuring the extent to which each of these correlations are present in space-time patches and whether they are coherent across spatiotemporal scales. We apply this technique to several popular movies. The results show that all three kinds of local motion signals are present in natural movies. While the balance of the different kinds of motion signals varies from segment to segment during the course of each movie, the overall pattern of prevalence of the different kinds of motion and their subtypes, and the correlations between them, is strikingly similar across movies (but is absent from white noise movies). In sum, naturalistic movies contain a diversity of local motion signals that occur with a consistent prevalence and pattern of covariation, indicating a substantial regularity of their high-order spatiotemporal image statistics

Online learning of causal structure in a dynamic game situation

Agents situated in a dynamic environment with an initially unknown causal structure, which, moreover, links certain behavioral choices to rewards, must be able to learn such structure incrementally on the fly. We report an experimental study that characterizes human learning in a controlled dynamic game environment, and describe a computational model that is capable of similar learning. The model learns by building up a representation of the hypothesized causes and effects, including estimates of the strength of each causal interaction. It is driven initially by simple guesses regarding such interactions, inspired by events occurring in close temporal succession. The model maintains its structure dynamically (including omitting or even reversing the current best-guess dependencies, if warranted by new evidence), and estimates the projected probability of possible outcomes by performing inference on the resulting Bayesian network. The model reproduces the human performance in the present dynamical task