Internal logic viewed from observation space: Theory and a case study

We propose a framework of neurocognitive experiments that clarifies the mathematical struc-ture of experiments and can be used to analyze experimental results and to determine the limitation of their possible interpretation. In contrast to the conventional analysis that em-ploys simple Boolean logic, the present analysis treats classification in terms of higher-order functions. We also predict the existence of a previously unidentified type of neuron

Functional differentiations in evolutionary reservoir computing networks

We propose an extended reservoir computer that shows the functional differentiation of neurons. The reservoir computer is developed to enable changing of the internal reservoir using evolutionary dynamics, and we call it an evolutionary reservoir computer. To develop neuronal units to show specificity, depending on the input information, the internal dynamics should be controlled to produce contracting dynamics after expanding dynamics. Expanding dynamics magnifies the difference of input information, while contracting dynamics contributes to forming clusters of input information, thereby producing multiple attractors. The simultaneous appearance of both dynamics indicates the existence of chaos. In contrast, sequential appearance of these dynamics during finite time intervals may induce functional differentiations. In this paper, we show how specific neuronal units are yielded in the evolutionary reservoir computer.Comment: Revised manuscript. 15 figures. This article has been submitted to Chaos. After it is published, it will be found at https://aip.scitation.org/journal/ch

Analyzing Spatio-temporal Patterns of Epileptic EEG Signals by Dynamic Mode Decomposition (Mathematical study on Epilepsy)

In this work, we apply a dynamic mode decomposition (DMD) to epileptic EEG data to figure out the spatio-temporal patterns in the data. It is found that some patterns with high frequency have direct influence on the epileptic seizure, and instantaneously capture the abnormal patterns of the neuron firing with high precision. We prepare an ictal and interictal EEG data for an epileptic patient, and investigating the dyamics of the DMD modes captured by the proposed algorithm for the windowed EEG signals. From the results we conclude that the DMD modes extracted from the EEG signals can be useful for analyzing and understanding the dynamics of the epileptic EEG data

Ultra Low Loss Trench Gate PCI-PiN Diode with VF<350mV

PiN diode forward voltage drop was reduced to as low as 325mV by the pulsed carrier injection (PCI) mechanism with trench MOS gate as the integrated injection control switch. The conventional PiN diodes have voltage drop of about 0.8V which is equivalent to 1%-2% energy loss in home appliances. The proposed PCI-PiN diode reduces the loss by more than 50% and the diode structure has process compatibility to conventional IGBTs and trench MOSFETs for easy implementation into mass production. The authors also confirmed PCI concept with the experiment with BSIT.2011 23rd International Symposium on Power Semiconductor Devices & Ics (ISPSD. 2011), May 23?26, 2011, San Diego, California, US

In-Out Intermittency in Gap Junction-Coupled Class I^* Neurons

In a series of papers, we have proposed a dynamical model for gap junction-coupled networks of class I^* neurons, and investigated its dynamic characters. We found various dynamic states in a model neural network with diffusively coupled class I¤ neuron models, called μ-models. Among others, hierarchies of intermittent transitions attracted attention in relation with real brain dynamics. This paper is devoted to report a mechanism of the first transition appeared in the intermittenly transitory dynamics among an all-synchronized state, various metachronal waves and a weakly chaotic state. We clarify that this intermittent transition is described as an in-out intermittency

Visual hallucinations in dementia with Lewy bodies originate from necrosis of characteristic neurons and connections in three-module perception model

Mathematical and computational approaches were used to investigate dementia with Lewy bodies (DLB), in which recurrent complex visual hallucinations (RCVH) is a very characteristic symptom. Beginning with interpretative analyses of pathological symptoms of patients with RCVH-DLB in comparison with the veridical perceptions of normal subjects, we constructed a three-module scenario concerning function giving rise to perception. The three modules were the visual input module, the memory module, and the perceiving module. Each module interacts with the others, and veridical perceptions were regarded as a certain convergence to one of the perceiving attractors sustained by self-consistent collective fields among the modules. Once a rather large but inhomogeneously distributed area of necrotic neurons and dysfunctional synaptic connections developed due to network disease, causing irreversible damage, then bottom-up information from the input module to both the memory and perceiving modules were severely impaired. These changes made the collective fields unstable and caused transient emergence of mismatched perceiving attractors. This may account for the reason why DLB patients see things that are not there. With the use of our computational model and experiments, the scenario was recreated with complex bifurcation phenomena associated with the destabilization of collective field dynamics in very high-dimensional state space

Efficient Model Selection for Predictive Pattern Mining Model by Safe Pattern Pruning

Predictive pattern mining is an approach used to construct prediction models when the input is represented by structured data, such as sets, graphs, and sequences. The main idea behind predictive pattern mining is to build a prediction model by considering substructures, such as subsets, subgraphs, and subsequences (referred to as patterns), present in the structured data as features of the model. The primary challenge in predictive pattern mining lies in the exponential growth of the number of patterns with the complexity of the structured data. In this study, we propose the Safe Pattern Pruning (SPP) method to address the explosion of pattern numbers in predictive pattern mining. We also discuss how it can be effectively employed throughout the entire model building process in practical data analysis. To demonstrate the effectiveness of the proposed method, we conduct numerical experiments on regression and classification problems involving sets, graphs, and sequences

An Annotated List of Culicoides Biting Midges in Yaeyama Islands in the Southwestern Part of Japan (Diptera: Ceratopogonidae)

Species of Culicoides biting midges (Diptera: Ceratopogonidae) in Yaeyama Islands were listed. In total, 36 species were included in the list, in which C. palpifer Das Gupta and Ghosh was new to Japan and C. cylindratus Kitaoka, C. malayae Macfie and C. sasai Kitaoka were new to the islands. Taxonomic and biological notes for some species were also given