Jun Kitazono
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View article: Unsupervised alignment reveals structural commonalities and differences in neural representations of natural scenes across individuals and brain areas
Unsupervised alignment reveals structural commonalities and differences in neural representations of natural scenes across individuals and brain areas Open
View article: Association of Bidirectional Network Cores in the Brain with Perceptual Awareness and Cognition
Association of Bidirectional Network Cores in the Brain with Perceptual Awareness and Cognition Open
The brain comprises a complex network of interacting regions. To understand the roles and mechanisms of this intricate network, it is crucial to elucidate its structural features related to cognitive functions. Recent empirical evidence su…
View article: Exploring state-dependent controllable directions and magnitudes: a network control theory approach to TMS-EEG responses
Exploring state-dependent controllable directions and magnitudes: a network control theory approach to TMS-EEG responses Open
View article: Association of bidirectional network cores in the brain with perceptual awareness and cognition
Association of bidirectional network cores in the brain with perceptual awareness and cognition Open
The brain comprises a complex network of interacting regions. To understand the roles and mechanisms of this intricate network, it is crucial to elucidate its structural features related to cognitive functions. Recent empirical evidence su…
View article: Unsupervised Alignment Reveals Structural Commonalities and Differences in Neural Representations of Natural Scenes Across Individuals and Brain Areas
Unsupervised Alignment Reveals Structural Commonalities and Differences in Neural Representations of Natural Scenes Across Individuals and Brain Areas Open
View article: Single-cell resolution functional networks during unconsciousness are segregated into spatially intermixed modules
Single-cell resolution functional networks during unconsciousness are segregated into spatially intermixed modules Open
The common neural mechanisms underlying the reduction of consciousness during sleep and anesthesia remain unclear. Previous studies have examined changes in network structure only using recordings with limited spatial resolution, which has…
View article: A New Framework for System Core Extraction
A New Framework for System Core Extraction Open
View article: Optimal Control Costs of Brain State Transitions in Linear Stochastic Systems
Optimal Control Costs of Brain State Transitions in Linear Stochastic Systems Open
The brain is a system that performs numerous functions by controlling its states. Quantifying the cost of this control is essential as it reveals how the brain can be controlled based on the minimization of the control cost, and which brai…
View article: Bidirectionally connected cores in a mouse connectome: towards extracting the brain subnetworks essential for consciousness
Bidirectionally connected cores in a mouse connectome: towards extracting the brain subnetworks essential for consciousness Open
Where in the brain consciousness resides remains unclear. It has been suggested that the subnetworks supporting consciousness should be bidirectionally (recurrently) connected because both feed-forward and feedback processing are necessary…
View article: Optimal Control Costs of Brain State Transitions in Linear Stochastic Systems
Optimal Control Costs of Brain State Transitions in Linear Stochastic Systems Open
The brain is a system that performs numerous functions by controlling its states. Quantifying the cost of this control is essential as it reveals how the brain can be controlled based on the minimization of the control cost, and which brai…
View article: Quantifying brain state transition cost via Schrödinger Bridge
Quantifying brain state transition cost via Schrödinger Bridge Open
Quantifying brain state transition cost is a fundamental problem in systems neuroscience. Previous studies utilized network control theory to measure the cost by considering a neural system as a deterministic dynamical system. However, thi…
View article: Bidirectionally connected cores in a mouse connectome: Towards extracting the brain subnetworks essential for consciousness
Bidirectionally connected cores in a mouse connectome: Towards extracting the brain subnetworks essential for consciousness Open
Where in the brain consciousness resides remains unclear. It has been suggested that the subnetworks supporting consciousness should be bidirectionally (recurrently) connected because both feed-forward and feedback processing are necessary…
View article: Efficient search for informational cores in complex systems: Application to brain networks
Efficient search for informational cores in complex systems: Application to brain networks Open
An important step in understanding the nature of the brain is to identify "cores" in the brain network, where brain areas strongly interact with each other. Cores can be considered as essential sub-networks for brain functions. In the last…
View article: Efficient search for informational cores in complex systems: Application to brain networks
Efficient search for informational cores in complex systems: Application to brain networks Open
To understand the nature of the complex behavior of the brain, one important step is to identify “cores” in the brain network, where neurons or brain areas strongly interact with each other. Cores can be considered as essential sub-network…
View article: An Exhaustive Search and Stability of Sparse Estimation for Feature Selection Problem
An Exhaustive Search and Stability of Sparse Estimation for Feature Selection Problem Open
Feature selection problem has been widely used for various fields. In particular, the sparse estimation has the advantage that its computational cost is the polynomial order of the number of features. However, it has the problem that the o…
View article: Large-Scale Monitoring for Cyber Attacks by Using Cluster Information on Darknet Traffic Features
Large-Scale Monitoring for Cyber Attacks by Using Cluster Information on Darknet Traffic Features Open
This paper presents a machine learning approach to large-scale monitoring for malicious activities on Internet. In the proposed system, network packets sent from a subnet to a darknet (i.e., a set of unused IPs) are collected, and they are…