Transformation from natural (thermal contraction) to anthropogenic (resource exploitation) depressions in the Krotoszyn-Koźmin-Raszków area (Polish Lowland)

An exceptional concentration of almost identical depressions exist near the small towns of Krotoszyn, Koźmin and Raszków (southern Wielkopolska). Their origin is, however, different from that of the typical post glacial-relief: they are Man-made enlarged thermal-contraction structures that developed at the very end of the Middle Polish (Warthian) glaciation and during the North Polish (Weichselian) glaciation, most probably under periglacial conditions.

Dynamic Server Selection using Bandwidth Probing in Wide-Area Networks

Replication is a commonly proposed solution to problems of scale associated with distributed services. However, when a service is replicated, each client must be assigned a server. Prior work has generally assumed that assignment to be static. In contrast, we propose dynamic server selection, and show that it enables application-level congestion avoidance. To make dynamic server selection practical, we demonstrate the use of three tools. In addition to direct measurements of round-trip latency, we introduce and validate two new tools: bprobe, which estimates the maximum possible bandwidth along a given path; and cprobe, which estimates the current congestion along a path. Using these tools we demonstrate dynamic server selection and compare it to previous static approaches. We show that dynamic server selection consistently outperforms static policies by as much as 50%. Furthermore, we demonstrate the importance of each of our tools in performing dynamic server selection.

Measuring Web Performance in the Wide Area

One of the most vexing questions facing researchers interested in the World Wide Web is why users often experience long delays in document retrieval. The Internet's size, complexity, and continued growth make this a difficult question to answer. We describe the Wide Area Web Measurement project (WAWM) which uses an infrastructure distributed across the Internet to study Web performance. The infrastructure enables simultaneous measurements of Web client performance, network performance and Web server performance. The infrastructure uses a Web traffic generator to create representative workloads on servers, and both active and passive tools to measure performance characteristics. Initial results based on a prototype installation of the infrastructure are presented in this paper.

A Laminar Cortical Model for 3D Perception of Slanted and Curved Surfaces and of 2D Images: Developement, attention, and Bistability

A model of laminar visual cortical dynamics proposes how 3D boundary and surface representations of slated and curved 3D objects and 2D images arise. The 3D boundary representations emerge from interactions between non-classical horizontal receptive field interactions with intracorticcal and intercortical feedback circuits. Such non-classical interactions contextually disambiguate classical receptive field responses to ambiguous visual cues using cells that are sensitive to angles and disparity gradients with cortical areas V1 and V2. These cells are all variants of bipole grouping cells. Model simulations show how horizontal connections can develop selectively to angles, how slanted surfaces can activate 3D boundary representations that are sensitive to angles and disparity gradients, how 3D filling-in occurs across slanted surfaces, how a 2D Necker cube image can be represented in 3D, and how bistable Necker cuber percepts occur. The model also explains data about slant aftereffects and 3D neon color spreading. It shows how habituative transmitters that help to control developement also help to trigger bistable 3D percepts and slant aftereffects, and how attention can influence which of these percepts is perceived by propogating along some object boundaries.

A Cortical and Cerebellar Parcellation System for Speech Studies

A neuroanatomical parcellation system is described which encompasses the entire cerebral cortex and the cerebellum. The cortical system modified version of the scheme described by Caviness et al. (1996) and is designed particularly for studies of speech processing. The cerebellum is parcellated into 6 cortical regions of interest (ROIs) and an ROI representing the deep cerebellar nuclei in each hemisphere. The boundaries of each ROI are based on individual anatomical markers that are clearly visible from standard structural MRI acquistions. The system permits averaginh of functional imaging data sets from multiple sujects while accounting for individual anatomical variability. Used in conjuction with region-of-interest analysis techniques such as that described by Nieto-Castanon et al. (2003), the parcellation system provides a more powerful means of analyzing functional data.

Laminar Cortical Dynamics of 3D Surface Perception: Stratification, transparency, and Neon Color Spreading

How does the laminar organization of cortical circuitry in areas VI and V2 give rise to 3D percepts of stratification, transparency, and neon color spreading in response to 2D pictures and 3D scenes? Psychophysical experiments have shown that such 3D percepts are sensitive to whether contiguous image regions have the same relative contrast polarity (dark-light or lightdark), yet long-range perceptual grouping is known to pool over opposite contrast polarities. The ocularity of contiguous regions is also critical for neon color spreading: Having different ocularity despite the contrast relationship that favors neon spreading blocks the spread. In addition, half visible points in a stereogram can induce near-depth transparency if the contrast relationship favors transparency in the half visible areas. It thus seems critical to have the whole contrast relationship in a monocular configuration, since splitting it between two stereogram images cancels the effect. What adaptive functions of perceptual grouping enable it to both preserve sensitivity to monocular contrast and also to pool over opposite contrasts? Aspects of cortical development, grouping, attention, perceptual learning, stereopsis and 3D planar surface perception have previously been analyzed using a 3D LAMINART model of cortical areas VI, V2, and V4. The present work consistently extends this model to show how like-polarity competition between VI simple cells in layer 4 may be combined with other LAMINART grouping mechanisms, such as cooperative pooling of opposite polarities at layer 2/3 complex cells. The model also explains how the Metelli Rules can lead to transparent percepts, how bistable transparency percepts can arise in which either surface can be perceived as transparent, and how such a transparency reversal can be facilitated by an attention shift. The like-polarity inhibition prediction is consistent with lateral masking experiments in which two f1anking Gabor patches with the same contrast polarity as the target increase the target detection threshold when they approach the target. It is also consistent with LAMINART simulations of cortical development. Other model explanations and testable predictions will also be presented.

Fast Synchronization of Perpetual Grouping in Laminar Visual Cortical Circuits

Perceptual grouping is well-known to be a fundamental process during visual perception, notably grouping across scenic regions that do not receive contrastive visual inputs. Illusory contours are a classical example of such groupings. Recent psychophysical and neurophysiological evidence have shown that the grouping process can facilitate rapid synchronization of the cells that are bound together by a grouping, even when the grouping must be completed across regions that receive no contrastive inputs. Synchronous grouping can hereby bind together different object parts that may have become desynchronized due to a variety of factors, and can enhance the efficiency of cortical transmission. Neural models of perceptual grouping have clarified how such fast synchronization may occur by using bipole grouping cells, whose predicted properties have been supported by psychophysical, anatomical, and neurophysiological experiments. These models have not, however, incorporated some of the realistic constraints on which groupings in the brain are conditioned, notably the measured spatial extent of long-range interactions in layer 2/3 of a grouping network, and realistic synaptic and axonal signaling delays within and across cells in different cortical layers. This work addresses the question: Can long-range interactions that obey the bipole constraint achieve fast synchronization under realistic anatomical and neurophysiological constraints that initially desynchronize grouping signals? Can the cells that synchronize retain their analog sensitivity to changing input amplitudes? Can the grouping process complete and synchronize illusory contours across gaps in bottom-up inputs? Our simulations show that the answer to these questions is Yes.

Modeling the Possible Influences of Eye Movements on the Refinement of Cortical Direction Selectivity

The second-order statistics of neural activity was examined in a model of the cat LGN and V1 during free-viewing of natural images. In the model, the specific patterns of thalamocortical activity required for a Bebbian maturation of direction-selective cells in VI were found during the periods of visual fixation, when small eye movements occurred, but not when natural images were examined in the absence of fixational eye movements. In addition, simulations of stroboscopic reming that replicated the abnormal pattern of eye movements observed in kittens chronically exposed to stroboscopic illumination produced results consistent with the reported loss of direction selectivity and preservation of orientation selectivity. These results suggest the involvement of the oculomotor activity of visual fixation in the maturation of cortical direction selectivity.

How Does Binocular Rivalry Emerge from Cortical Mechanisms of 3D Vision?

Under natural viewing conditions, a single depthful percept of the world is consciously seen. When dissimilar images are presented to corresponding regions of the two eyes, binocular rivalyr may occur, during which the brain consciously perceives alternating percepts through time. How do the same brain mechanisms that generate a single depthful percept of the world also cause perceptual bistability, notably binocular rivalry? What properties of brain representations correspond to consciously seen percepts? A laminar cortical model of how cortical areas V1, V2, and V4 generate depthful percepts is developed to explain and quantitatively simulate binocualr rivalry data. The model proposes how mechanisms of cortical developement, perceptual grouping, and figure-ground perception lead to signle and rivalrous percepts. Quantitative model simulations include influences of contrast changes that are synchronized with switches in the dominant eye percept, gamma distribution of dominant phase durations, piecemeal percepts, and coexistence of eye-based and stimulus-based rivalry. The model also quantitatively explains data about multiple brain regions involved in rivalry, effects of object attention on switching between superimposed transparent surfaces, and monocular rivalry. These data explanations are linked to brain mechanisms that assure non-rivalrous conscious percepts. To our knowledge, no existing model can explain all of these phenomena.

Dopaminergic and Non-Dopaminergic Value Systems in Conditioning and Outcome-Specific Revaluation

Animals are motivated to choose environmental options that can best satisfy current needs. To explain such choices, this paper introduces the MOTIVATOR (Matching Objects To Internal Values Triggers Option Revaluations) neural model. MOTIVATOR describes cognitiveemotional interactions between higher-order sensory cortices and an evaluative neuraxis composed of the hypothalamus, amygdala, and orbitofrontal cortex. Given a conditioned stimulus (CS), the model amygdala and lateral hypothalamus interact to calculate the expected current value of the subjective outcome that the CS predicts, constrained by the current state of deprivation or satiation. The amygdala relays the expected value information to orbitofrontal cells that receive inputs from anterior inferotemporal cells, and medial orbitofrontal cells that receive inputs from rhinal cortex. The activations of these orbitofrontal cells code the subjective values of objects. These values guide behavioral choices. The model basal ganglia detect errors in CS-specific predictions of the value and timing of rewards. Excitatory inputs from the pedunculopontine nucleus interact with timed inhibitory inputs from model striosomes in the ventral striatum to regulate dopamine burst and dip responses from cells in the substantia nigra pars compacta and ventral tegmental area. Learning in cortical and striatal regions is strongly modulated by dopamine. The model is used to address tasks that examine food-specific satiety, Pavlovian conditioning, reinforcer devaluation, and simultaneous visual discrimination. Model simulations successfully reproduce discharge dynamics of known cell types, including signals that predict saccadic reaction times and CS-dependent changes in systolic blood pressure.

Speaker Normalization Using Cortical Strip Maps: A Neural Model for Steady State Vowel Identification

Auditory signals of speech are speaker-dependent, but representations of language meaning are speaker-independent. Such a transformation enables speech to be understood from different speakers. A neural model is presented that performs speaker normalization to generate a pitchindependent representation of speech sounds, while also preserving information about speaker identity. This speaker-invariant representation is categorized into unitized speech items, which input to sequential working memories whose distributed patterns can be categorized, or chunked, into syllable and word representations. The proposed model fits into an emerging model of auditory streaming and speech categorization. The auditory streaming and speaker normalization parts of the model both use multiple strip representations and asymmetric competitive circuits, thereby suggesting that these two circuits arose from similar neural designs. The normalized speech items are rapidly categorized and stably remembered by Adaptive Resonance Theory circuits. Simulations use synthesized steady-state vowels from the Peterson and Barney [J. Acoust. Soc. Am. 24, 175-184 (1952)] vowel database and achieve accuracy rates similar to those achieved by human listeners. These results are compared to behavioral data and other speaker normalization models.

Cortical Learning of Recognition Categories: A Resolution of the Exemplar Vs. Prototype Debate

Do humans and animals learn exemplars or prototypes when they categorize objects and events in the world? How are different degrees of abstraction realized through learning by neurons in inferotemporal and prefrontal cortex? How do top-down expectations influence the course of learning? Thirty related human cognitive experiments (the 5-4 category structure) have been used to test competing views in the prototype-exemplar debate. In these experiments, during the test phase, subjects unlearn in a characteristic way items that they had learned to categorize perfectly in the training phase. Many cognitive models do not describe how an individual learns or forgets such categories through time. Adaptive Resonance Theory (ART) neural models provide such a description, and also clarify both psychological and neurobiological data. Matching of bottom-up signals with learned top-down expectations plays a key role in ART model learning. Here, an ART model is used to learn incrementally in response to 5-4 category structure stimuli. Simulation results agree with experimental data, achieving perfect categorization in training and a good match to the pattern of errors exhibited by human subjects in the testing phase. These results show how the model learns both prototypes and certain exemplars in the training phase. ART prototypes are, however, unlike the ones posited in the traditional prototype-exemplar debate. Rather, they are critical patterns of features to which a subject learns to pay attention based on past predictive success and the order in which exemplars are experienced. Perturbations of old memories by newly arriving test items generate a performance curve that closely matches the performance pattern of human subjects. The model also clarifies exemplar-based accounts of data concerning amnesia.

Laminar Cortical Dynamics of Cognitive and Motor Working Memory, Sequence Learning and Performance: Toward a Unified Theory of How the Cerebral Cortex Works

How do the layered circuits of prefrontal and motor cortex carry out working memory storage, sequence learning, and voluntary sequential item selection and performance? A neural model called LIST PARSE is presented to explain and quantitatively simulate cognitive data about both immediate serial recall and free recall, including bowing of the serial position performance curves, error-type distributions, temporal limitations upon recall, and list length effects. The model also qualitatively explains cognitive effects related to attentional modulation, temporal grouping, variable presentation rates, phonemic similarity, presentation of non-words, word frequency/item familiarity and list strength, distracters and modality effects. In addition, the model quantitatively simulates neurophysiological data from the macaque prefrontal cortex obtained during sequential sensory-motor imitation and planned performance. The article further develops a theory concerning how the cerebral cortex works by showing how variations of the laminar circuits that have previously clarified how the visual cortex sees can also support cognitive processing of sequentially organized behaviors.

Towards a Unified Theory of Neocortex: Laminar Cortical Circuits for Vision and Cognition

A key goal of computational neuroscience is to link brain mechanisms to behavioral functions. The present article describes recent progress towards explaining how laminar neocortical circuits give rise to biological intelligence. These circuits embody two new and revolutionary computational paradigms: Complementary Computing and Laminar Computing. Circuit properties include a novel synthesis of feedforward and feedback processing, of digital and analog processing, and of pre-attentive and attentive processing. This synthesis clarifies the appeal of Bayesian approaches but has a far greater predictive range that naturally extends to self-organizing processes. Examples from vision and cognition are summarized. A LAMINART architecture unifies properties of visual development, learning, perceptual grouping, attention, and 3D vision. A key modeling theme is that the mechanisms which enable development and learning to occur in a stable way imply properties of adult behavior. It is noted how higher-order attentional constraints can influence multiple cortical regions, and how spatial and object attention work together to learn view-invariant object categories. In particular, a form-fitting spatial attentional shroud can allow an emerging view-invariant object category to remain active while multiple view categories are associated with it during sequences of saccadic eye movements. Finally, the chapter summarizes recent work on the LIST PARSE model of cognitive information processing by the laminar circuits of prefrontal cortex. LIST PARSE models the short-term storage of event sequences in working memory, their unitization through learning into sequence, or list, chunks, and their read-out in planned sequential performance that is under volitional control. LIST PARSE provides a laminar embodiment of Item and Order working memories, also called Competitive Queuing models, that have been supported by both psychophysical and neurobiological data. These examples show how variations of a common laminar cortical design can embody properties of visual and cognitive intelligence that seem, at least on the surface, to be mechanistically unrelated.

Does Binocular Rivalry Emerge from Cortical Mechanisms of 3D Vision

Under natural viewing conditions, a single depthful percept of the world is consciously seen. When dissimilar images are presented to corresponding regions of the two eyes, binocular rivalry may occur, during which the brain consciously perceives alternating percepts through time. Perceptual bistability can also occur in response to a single ambiguous figure. These percepts raise basic questions: What brain mechanisms generate a single depthful percept of the world? How do the same mechanisms cause perceptual bistability, notably binocular rivalry? What properties of brain representations correspond to consciously seen percepts? How do the dynamics of the layered circuits of visual cortex generate single and bistable percepts? A laminar cortical model of how cortical areas V1, V2, and V4 generate depthful percepts is developed to explain and quantitatively simulate binocular rivalry data. The model proposes how mechanisms of cortical development, perceptual grouping, and figure-ground perception lead to single and rivalrous percepts.