Glosarium Matematika

273 p.; 24 cm

Ecological expected utility and the mythical neural code

Neural spikes are an evolutionarily ancient innovation that remains nature’s unique mechanism for rapid, long distance information transfer. It is now known that neural spikes sub serve a wide variety of functions and essentially all of the basic questions about the communication role of spikes have been answered. Current efforts focus on the neural communication of probabilities and utility values involved in decision making. Significant progress is being made, but many framing issues remain. One basic problem is that the metaphor of a neural code suggests a communication network rather than a recurrent computational system like the real brain. We propose studying the various manifestations of neural spike signaling as adaptations that optimize a utility function called ecological expected utility

GPU-based implementation of real-time system for spiking neural networks

Real-time simulations of biological neural networks (BNNs) provide a natural platform for applications in a variety of fields: data classification and pattern recognition, prediction and estimation, signal processing, control and robotics, prosthetics, neurological and neuroscientific modeling. BNNs possess inherently parallel architecture and operate in continuous signal domain. Spiking neural networks (SNNs) are type of BNNs with reduced signal dynamic range: communication between neurons occurs by means of time-stamped events (spikes). SNNs allow reduction of algorithmic complexity and communication data size at a price of little loss in accuracy. Simulation of SNNs using traditional sequential computer architectures results in significant time penalty. This penalty prohibits application of SNNs in real-time systems. Graphical processing units (GPUs) are cost effective devices specifically designed to exploit parallel shared memory-based floating point operations applied not only to computer graphics, but also to scientific computations. This makes them an attractive solution for SNN simulation compared to that of FPGA, ASIC and cluster message passing computing systems. Successful implementations of GPU-based SNN simulations have been already reported. The contribution of this thesis is the development of a scalable GPU-based realtime system that provides initial framework for design and application of SNNs in various domains. The system delivers an interface that establishes communication with neurons in the network as well as visualizes the outcome produced by the network. Accuracy of the simulation is emphasized due to its importance in the systems that exploit spike time dependent plasticity, classical conditioning and learning. As a result, a small network of 3840 Izhikevich neurons implemented as a hybrid system with Parker-Sochacki numerical integration method achieves real time operation on GTX260 device. An application case study of the system modeling receptor layer of retina is reviewed

The cognitive neuroscience of visual working memory

Visual working memory allows us to temporarily maintain and manipulate visual information in order to solve a task. The study of the brain mechanisms underlying this function began more than half a century ago, with Scoville and Milner’s (1957) seminal discoveries with amnesic patients. This timely collection of papers brings together diverse perspectives on the cognitive neuroscience of visual working memory from multiple fields that have traditionally been fairly disjointed: human neuroimaging, electrophysiological, behavioural and animal lesion studies, investigating both the developing and the adult brain

Mechanisms of memory formation and consolidation in hippocampal and cortical pyramidal mouse neurons

The roles of hippocampus and cortex in recent and remote memory processing is well assessed and the association of experience-dependent behavioural modifications with hippocampal and anterior cingulate cortical (ACC) neuron morphological changes at different time points after contextual fear conditioning has been characterised. Although the association between such morphological modifications and biochemical changes related deserves further characterisation. Here, we have previously observed that during the formation of recent contextual fear memory, hippocampal CA1 neurons display morphological changes in parallel with rapid accumulation of EphrinB2, a cell adhesion factor known, in association with its receptor(s), to influence synaptic plasticity and the dynamics of dendritic spines. To investigate whether this process may represent a general marker of induced neuronal plasticity, we studied the conversion of recent -to-remote memory, which ultimately depends on an increase in dendritic spine number of pyramidal neurons of the anterior cingulate cortex (ACC), by analysing the effect of contextual fear conditioning on EphrinB2 levels in these neurons. To this end, we determined dendritic complexity and EphrinB2 levels 24 hours (recent), 7 days (imtermediate) and 36 days (remote) after conditioning in C57BL/6N mice. We observed that EphrinB2 accumulation parallels the increase in spine density of CA1 neurons of conditioned mice, at the recent and intermediate time point, subsequently decreasing at the remote time point. In addition, a similar parallel pattern was observed for neuronal EphrinB2 levels and dendritic complexity in the ACC, which were both increased at the remote time point. The increase in EphrinB2 levels observed in the hipppocampus 24 hr post conditioning and in the ACC 36 days after was prevented by post-training anisomycin treatment. On the contrary, late anisomycin treatmen (24 days post conditioning) didn't prevent EphrinB2 increase in the cortex. These results suggest that accumulation of EphrinB2 is involved in memory-associated cellular modifications detected in both the hippocampus and ACC, and may therefore represent a more general biochemical marker of conditioning-induced neuronal rearrangements

Mechanisms of memory formation and consolidation in hippocampal and cortical pyramidal mouse neurons

The roles of hippocampus and cortex in recent and remote memory processing is well assessed and the association of experience-dependent behavioural modifications with hippocampal and anterior cingulate cortical (ACC) neuron morphological changes at different time points after contextual fear conditioning has been characterised. Although the association between such morphological modifications and biochemical changes related deserves further characterisation. Here, we have previously observed that during the formation of recent contextual fear memory, hippocampal CA1 neurons display morphological changes in parallel with rapid accumulation of EphrinB2, a cell adhesion factor known, in association with its receptor(s), to influence synaptic plasticity and the dynamics of dendritic spines. To investigate whether this process may represent a general marker of induced neuronal plasticity, we studied the conversion of recent -to-remote memory, which ultimately depends on an increase in dendritic spine number of pyramidal neurons of the anterior cingulate cortex (ACC), by analysing the effect of contextual fear conditioning on EphrinB2 levels in these neurons. To this end, we determined dendritic complexity and EphrinB2 levels 24 hours (recent), 7 days (imtermediate) and 36 days (remote) after conditioning in C57BL/6N mice. We observed that EphrinB2 accumulation parallels the increase in spine density of CA1 neurons of conditioned mice, at the recent and intermediate time point, subsequently decreasing at the remote time point. In addition, a similar parallel pattern was observed for neuronal EphrinB2 levels and dendritic complexity in the ACC, which were both increased at the remote time point. The increase in EphrinB2 levels observed in the hipppocampus 24 hr post conditioning and in the ACC 36 days after was prevented by post-training anisomycin treatment. On the contrary, late anisomycin treatmen (24 days post conditioning) didn't prevent EphrinB2 increase in the cortex. These results suggest that accumulation of EphrinB2 is involved in memory-associated cellular modifications detected in both the hippocampus and ACC, and may therefore represent a more general biochemical marker of conditioning-induced neuronal rearrangements

Representation Learning for Natural Language Processing

This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including words, phrases, sentences and documents. Part II then introduces the representation techniques for those objects that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, networks, and cross-modal entries. Lastly, Part III provides open resource tools for representation learning techniques, and discusses the remaining challenges and future research directions. The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, social network analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing

The development of bottom-up and top-down interaction in the processing of goal-directed action

The study of action-cognition is driven by the assumption that what one can do motorically depends on what one can conceive of mentally, given a set of external opportunities (Rosenbaum, Cohen, & Jax, 2007). Therefore, a comprehensive theory of action development ought to integrate perceptual aspects of action processing with conceptual changes that give rise to increasingly abstract behaviours. How and why children progress to higher levels of organization in the processing and coordination of purposeful behaviour is a question that has been at the core of developmental research for decades. Various competences underlying early action processing and decision-making have been identified and linked to sophisticated mental operations later in life. However, considerably less is known about the relationships between perceptual and conceptual abilities and how they interact to shape action development. Goal-pursuit is achieved with increasing efficiency during the preschool period. In fact, by the age of first grade children show substantial abilities to regulate actions into hierarchically structured sequences of events that can be transferred across contexts (e.g., Levy, 1980; Bell & Livesey, 1985; Livesey & Morgan, 1991). The aim of this project was to investigate the perceptual and conceptual processes that drive these remarkable advances as they emerge during the preschool years. The studies in this thesis investigate top-down and bottom-up interactions in the processing of actions at various levels of abstraction. Employing a range of novel paradigms, the results of four studies highlight considerable advances in preschoolers’ abilities to organise actions in terms of goal hierarchies. Findings further highlight that the ability to extract structure at a basic level is readily achieved early in life, while higher-level action comprehension and planning abilities continue to develop throughout the childhood years