The role of terminators and occlusion cues in motion integration and segmentation: a neural network model

The perceptual interaction of terminators and occlusion cues with the functional processes of motion integration and segmentation is examined using a computational model. Inte-gration is necessary to overcome noise and the inherent ambiguity in locally measured motion direction (the aperture problem). Segmentation is required to detect the presence of motion discontinuities and to prevent spurious integration of motion signals between objects with different trajectories. Terminators are used for motion disambiguation, while occlusion cues are used to suppress motion noise at points where objects intersect. The model illustrates how competitive and cooperative interactions among cells carrying out these functions can account for a number of perceptual effects, including the chopsticks illusion and the occluded diamond illusion. Possible links to the neurophysiology of the middle temporal visual area (MT) are suggested

Hands-On Universe: A Global Program for Education and Public Outreach in Astronomy

Hands-On Universe (HOU) is an educational program that enables students to investigate the Universe while applying tools and concepts from science, math, and technology. Using the Internet, HOU participants around the world request observations from an automated telescope, download images from a large image archive, and analyze them with the aid of user-friendly image processing software. This program is developing now in many countries, including the USA, France, Germany, Sweden, Japan, Australia, and others. A network of telescopes has been established among these countries, many of them remotely operated, as shown in the accompanying demo. Using this feature, students in the classroom are able to make night observations during the day, using a telescope placed in another country. An archive of images taken on large telescopes is also accessible, as well as resources for teachers. Students are also dealing with real research projects, e.g. the search for asteroids, which resulted in the discovery of a Kuiper Belt object by high-school students. Not only Hands-On Universe gives the general public an access to professional astronomy, but it is also a more general tool to demonstrate the use of a complex automated system, the techniques of data processing and automation. Last but not least, through the use of telescopes located in many countries over the globe, a form of powerful and genuine cooperation between teachers and children from various countries is promoted, with a clear educational goal.Comment: 4 pages, 1 figure, to appear in the proceedings of the ADASS X conference, Boston, October 2000, ASP conf. pro

Computing action equivalences for planning under time-constraints

In order for autonomous artificial decision-makers to solverealistic tasks, they need to deal with the dual problems of searching throughlarge state and action spaces under time pressure.We study the problem of planning in domains with lots of objects. Structuredrepresentations of action can help provide guidance when the number of actionchoices and size of the state space is large.We show how structured representations ofaction effects can help us partition the action space in to a smallerset of approximate equivalence classes. Then, the pared-downaction space can be used to identify a useful subset of the state space in whichto search for a solution. As computational resources permit, we thenallow ourselves to elaborate the original solution. This kind of analysisallows us to collapse the action space and permits faster planning in muchlarger domains than before

Adaptive Envelope MDPs for Relational Equivalence-based Planning

We describe a method to use structured representations of the environmentâs dynamics to constrain and speed up the planning process. Given a problem domain described in a probabilistic logical description language, we develop an anytime technique that incrementally improves on an initial, partial policy. This partial solution is found by ï¬rst reducing the number of predicates needed to represent a relaxed version of the problem to a minimum, and then dynamically partitioning the action space into a set of equivalence classes with respect to this minimal representation. Our approach uses the envelope MDP framework, which creates a Markov decision process out of a subset of the full state space as de- termined by the initial partial solution. This strategy permits an agent to begin acting within a restricted part of the full state space and to expand its envelope judiciously as resources permit

Two-dimensional protein crystallization via metal-ion coordination by naturally occurring surface histidines

A powerful and potentially general approach to the targeting and crystallization of proteins on lipid interfaces through coordination of surface histidine residues to lipid-chelated divalent metal ions is presented. This approach, which should be applicable to the crystallization of a wide range of naturally occurring or engineered proteins, is illustrated here by the crystallization of streptavidin on a monolayer of an iminodiacetate-Cu(II) lipid spread at the air-water interface. This method allows control of the protein orientation at interfaces, which is significant for the facile production of highly ordered protein arrays and for electron density mapping in structural analysis of two-dimensional crystals. Binding of native streptavidin to the iminodiacetate-Cu lipids occurs via His-87, located on the protein surface near the biotin binding pocket. The two-dimensional streptavidin crystals show a previously undescribed microscopic shape that differs from that of crystals formed beneath biotinylated lipids

Learning with Deictic Representation

Most reinforcement learning methods operate on propositional representations of the world state. Such representations are often intractably large and generalize poorly. Using a deictic representation is believed to be a viable alternative: they promise generalization while allowing the use of existing reinforcement-learning methods. Yet, there are few experiments on learning with deictic representations reported in the literature. In this paper we explore the effectiveness of two forms of deictic representation and a naive propositional representation in a simple blocks-world domain. We find, empirically, that the deictic representations actually worsen performance. We conclude with a discussion of possible causes of these results and strategies for more effective learning in domains with objects

Reply to Comment by Jonathan J. Rhodes on ‘‘Modeling of the Interactions between Forest Vegetation, Disturbances, and Sediment Yields’’

Rhodes [2005] brings up some excellent points in his comments on the work of Istanbulluoglu et al. [2004]. We appreciate the opportunity to respond because it is likely that other readers will also wonder how they can apply the relatively simple analysis to important policy questions. Models necessarily reduce the complexity of the problem to make it tractable and synthesize some diverse sources of information. It may be helpful at times for readers to understand the high dimension of the complexity sacrificed in order to obtain the synthesis and the reasons for reducing the complexity in a particular manner. Rhodes [2005] comments on three things: (1) the omission of roads and landings from the analysis; (2) the implicit assumption that fire does not occur with harvesting; and (3) the overestimation of water repellency. We will respond to each of these, clarifying and elaborating on the basis for our modeling choices

EEG Slow Waves in Traumatic Brain Injury: Convergent Findings in Mouse and Man

OBJECTIVE: Evidence from previous studies suggests that greater sleep pressure, in the form of EEG-based slow waves, accumulates in specific brain regions that are more active during prior waking experience. We sought to quantify the number and coherence of EEG slow waves in subjects with mild traumatic brain injury (mTBI). METHODS: We developed a method to automatically detect individual slow waves in each EEG channel, and validated this method using simulated EEG data. We then used this method to quantify EEG-based slow waves during sleep and wake states in both mouse and human subjects with mTBI. A modified coherence index that accounts for information from multiple channels was calculated as a measure of slow wave synchrony. RESULTS: Brain-injured mice showed significantly higher theta:alpha amplitude ratios and significantly more slow waves during spontaneous wakefulness and during prolonged sleep deprivation, compared to sham-injured control mice. Human subjects with mTBI showed significantly higher theta:beta amplitude ratios and significantly more EEG slow waves while awake compared to age-matched control subjects. We then quantified the global coherence index of slow waves across several EEG channels in human subjects. Individuals with mTBI showed significantly less EEG global coherence compared to control subjects while awake, but not during sleep. EEG global coherence was significantly correlated with severity of post-concussive symptoms (as assessed by the Neurobehavioral Symptom Inventory scale). CONCLUSION AND IMPLICATIONS: Taken together, our data from both mouse and human studies suggest that EEG slow wave quantity and the global coherence index of slow waves may represent a sensitive marker for the diagnosis and prognosis of mTBI and post-concussive symptoms

EEG Slow Waves in Traumatic Brain Injury: Convergent Findings in Mouse and Man

OBJECTIVE: Evidence from previous studies suggests that greater sleep pressure, in the form of EEG-based slow waves, accumulates in specific brain regions that are more active during prior waking experience. We sought to quantify the number and coherence of EEG slow waves in subjects with mild traumatic brain injury (mTBI). METHODS: We developed a method to automatically detect individual slow waves in each EEG channel, and validated this method using simulated EEG data. We then used this method to quantify EEG-based slow waves during sleep and wake states in both mouse and human subjects with mTBI. A modified coherence index that accounts for information from multiple channels was calculated as a measure of slow wave synchrony. RESULTS: Brain-injured mice showed significantly higher theta:alpha amplitude ratios and significantly more slow waves during spontaneous wakefulness and during prolonged sleep deprivation, compared to sham-injured control mice. Human subjects with mTBI showed significantly higher theta:beta amplitude ratios and significantly more EEG slow waves while awake compared to age-matched control subjects. We then quantified the global coherence index of slow waves across several EEG channels in human subjects. Individuals with mTBI showed significantly less EEG global coherence compared to control subjects while awake, but not during sleep. EEG global coherence was significantly correlated with severity of post-concussive symptoms (as assessed by the Neurobehavioral Symptom Inventory scale). CONCLUSION AND IMPLICATIONS: Taken together, our data from both mouse and human studies suggest that EEG slow wave quantity and the global coherence index of slow waves may represent a sensitive marker for the diagnosis and prognosis of mTBI and post-concussive symptoms

Motor control by precisely timed spike patterns

A fundamental problem in neuroscience is to understand how sequences of action potentials ("spikes") encode information about sensory signals and motor outputs. Although traditional theories of neural coding assume that information is conveyed by the total number of spikes fired (spike rate), recent studies of sensory and motor activity have shown that far more information is carried by the millisecond-scale timing patterns of action potentials (spike timing). However, it is unknown whether or how subtle differences in spike timing drive differences in perception or behavior, leaving it unclear whether the information carried by spike timing actually plays a causal role in brain function. Here we demonstrate how a precise spike timing code is read out downstream by the muscles to control behavior. We provide both correlative and causal evidence to show that the nervous system uses millisecond-scale variations in the timing of spikes within multi-spike patterns to regulate a relatively simple behavior - respiration in the Bengalese finch, a songbird. These findings suggest that a fundamental assumption of current theories of motor coding requires revision, and that significant improvements in applications, such as neural prosthetic devices, can be achieved by using precise spike timing information.Comment: 48 pages, 16 figure