Biomedical subjects

Masato Okada

Publications and source records attributed to Masato Okada.

At least 19 recordsLinked to original sources

PubMed2026

ALID score for treatment-effect heterogeneity of adjunctive low-voltage area ablation in persistent atrial fibrillation: A post hoc analysis of SUPPRESS-AF.

BACKGROUND: In persistent atrial fibrillation (AF), the incremental benefit of adjunctive low-voltage area (LVA) ablation beyond pulmonary vein isolation (PVI) remains inconsistent. OBJECTIVE: To examine whether a simple clinical score characterizes treatment-effect heterogeneity of adjunctive LVA ablation among patients with mapped LVA > 5 cm2 and to perform an exploratory supportive analysis in an independent randomized cohort. METHODS: In this post-hoc analysis of SUPPRESS-AF, which included patients with persistent AF and mapped LVA > 5 cm2 after PVI, four variables-age ≥ 75 years, left atrial diameter > 44 mm, estimated glomerular filtration rate < 60 mL/min/1.73 m2, and absence of diabetes-were combined into the ALID score (0-4). Patients were stratified into low (0-1), intermediate (2), and high (3-4) score groups. Because EARNEST-PVI did not use LVA-guided ablation or select patients based on mapped LVA, it was analyzed as an exploratory supportive cohort rather than as an external validation cohort. RESULTS: In SUPPRESS-AF (n = 336), a significant treatment-by-score interaction was observed (P < 0.001). Adjunctive LVA ablation was associated with increased recurrence in the low-score stratum (HR 3.92; 95% CI 1.50-10.20) and reduced recurrence in the high-score stratum (HR 0.48; 95% CI 0.26-0.86). In EARNEST-PVI (n = 494), a qualitatively similar interaction pattern was observed for additional ablation beyond PVI (interaction P = 0.029), although the ablation strategy differed from LVA-guided ablation. CONCLUSIONS: Among patients with persistent AF and mapped LVA >5 cm2, the ALID score identified heterogeneity in response to adjunctive LVA ablation. These hypothesis-generating findings require prospective validation before clinical implementation.

Humans↗

PubMed2004

Population dynamics of face-responsive neurons in the inferior temporal cortex.

Neurons in the inferior temporal (IT) cortex of monkeys respond selectively to complex visual stimuli, such as faces. Single neurons in the IT cortex encode different kinds of information about visual stimuli in their temporal firing patterns. To understand the temporal aspects of the information encoded at a population level in the IT cortex, we applied principal component analysis (PCA) to the responses of a population of neurons. The responses of each neuron were recorded while visual stimuli that consisted of geometric shapes and faces of humans and monkeys were presented. We found that global categorization, i.e. human faces versus monkey faces versus shapes, occurred in the earlier part of the population response, and that fine categorization occurred within each member of the global category in the later part of the population response. A cluster analysis, a mixture of Gaussians analysis, confirmed that the clusters in the earlier part of the responses represented the global category. Moreover, the clusters in the earlier part separated into sub-clusters corresponding to either human identity or monkey expression in the later part of the responses, and the global categorization was maintained even after the appearance of the sub-clusters. The results suggest that a hierarchical relationship of the test stimuli is represented temporally by the population response of IT neurons.

Animals↗

PubMed2004

Bifurcation analysis in an associative memory model.

We previously reported the chaos induced by the frustration of interaction in a nonmonotonic sequential associative memory model, and showed the chaotic behaviors at absolute zero. We have now analyzed bifurcation in a stochastic system, namely, a finite-temperature model of the nonmonotonic sequential associative memory model. We derived order-parameter equations from the stochastic microscopic equations. Two-parameter bifurcation diagrams obtained from those equations show the coexistence of attractors, which do not appear at absolute zero, and the disappearance of chaos due to the temperature effect.

Journal Article↗

PubMed2004

Pulse-coupled resonate-and-fire models.

We analyze two pulse-coupled resonate-and-fire neurons. Numerical simulation reveals that an antiphase state is an attractor of this model. We can analytically explain the stability of antiphase states by means of a return map of firing times, which we propose in this paper. The resultant stability condition turns out to be quite simple. The phase diagram based on our theory shows that there are two types of antiphase states. One of these cannot be seen in coupled integrate-and-fire models and is peculiar to resonate-and-fire models. The results of our theory coincide with those of numerical simulations.

Action Potentials↗

PubMed2004

Activation of Cdc42 by trans interactions of the cell adhesion molecules nectins through c-Src and Cdc42-GEF FRG.

Nectins, Ca2+ -independent immunoglobulin-like cell-cell adhesion molecules, initiate cell-cell adhesion by their trans interactions and recruit cadherins to cooperatively form adherens junctions (AJs). In addition, the trans interactions of nectins induce the activation of Cdc42 and Rac small G proteins, which increases the velocity of the formation of AJs. We examined here how nectins induce the activation of Cdc42 in MDCK epithelial cells and L fibroblasts. Nectins recruited and activated c-Src at the nectin-based cell-cell adhesion sites. FRG, a GDP/GTP exchange factor specific for Cdc42, was then recruited there, tyrosine phosphorylated by c-Src, and activated, causing an increase in the GTP-bound active form of Cdc42. Inhibition of the nectin-induced activation of c-Src suppressed the nectin-induced activation of FRG and Cdc42. Inhibition of the nectin-induced activation of FRG or depletion of FRG by RNA interference suppressed the nectin-induced activation of Cdc42. These results indicate that nectins induce the activation of Cdc42 through c-Src and FRG locally at the nectin-based cell-cell adhesion sites.

Animals↗

PubMed2004

Dynamics of the adaptive natural gradient descent method for soft committee machines.

Adaptive natural gradient descent (ANGD) method realizes natural gradient descent (NGD) without needing to know the input distribution of learning data and reduces the calculation cost from a cubic order to a square order. However, no performance analysis of ANGD has been done. We have developed a statistical-mechanical theory of the simplified version of ANGD dynamics for soft committee machines in on-line learning; this method provides deterministic learning dynamics expressed through a few order parameters, even though ANGD intrinsically holds a large approximated Fisher information matrix. Numerical results obtained using this theory were consistent with those of a simulation, with respect not only to the learning curve but also to the learning failure. Utilizing this method, we numerically evaluated ANGD efficiency and found that ANGD generally performs as well as NGD. We also revealed the key condition affecting the learning plateau in ANGD.

Journal Article↗

PubMed2004

Coexistence of memory patterns and mixed states in a sparsely encoded associative memory model storing ultrametric patterns.

Analyzing the coexistence of memory patterns and mixed states gives important information for constructing a model for the face responsive neurons of the monkey inferior-temporal cortex. We analyzed whether the memory patterns coexist with mixed states when the sparse coding scheme is used for the associative memory model storing ultrametric patterns. For memory patterns and mixed states to coexist, there must be sufficient capacity for storing them and their threshold values must be the same. We determined that the storage capacities for all mixed states composed of correlated memory patterns diverge as 1/| f log f| (where f is the firing rate) even when the correlation of the memory patterns is infinitesimally small. We also determined that the memory patterns and the mixed states can become the equilibrium state of the model in the same threshold value. These results mean that they can coexist in this model. These findings should contribute to research on face responsive neurons in the monkey inferior-temporal cortex.

Action Potentials↗

PubMed2004

Csk defines the ability of integrin-mediated cell adhesion and migration in human colon cancer cells: implication for a potential role in cancer metastasis.

Progression of human colon cancer is often associated with elevated expression and activity of the Src family tyrosine kinase (SFK). SFK is ordinarily in equilibrium between inactive and primed states by a balance of negative regulatory kinase Csk and its counteracting tyrosine phosphatase(s), both of which act on the regulatory C-terminal tyrosine of SFK. To evaluate the contribution of the regulatory system of SFK in cancer progression, we here modulated the equilibrium status of SFK by introducing wild-type or dominant-negative Csk in human epithelial colon cancer cells, HCT15 and HT29. Overexpression of wild-type Csk induced decreased SFK activation, increased cell-cell contacts mediated by E-cadherin, decreased the number of focal contacts and decreased cell adhesion/migration and in vitro invasiveness. Conversely, expression of a dominant-negative Csk resulted in elevated SFK activation, enhanced phosphorylation of FAK and paxilllin, enhanced cell scattering, an increased number of focal contacts, dramatic rearrangement of actin cytoskeleton and increased cell adhesion/migration and in vitro invasiveness. In these scattered cells, however, localization, expression and phosphorylation of either E-cadherin or beta-catenin were not significantly affected, suggesting that the E-cadherin-mediated cell-cell contact is indirectly regulated by SFK. Furthermore, all these events occurred absolutely dependent on integrin-mediated cell adhesion. These findings demonstrate that Csk defines the ability of integrin-SFK-mediated cell adhesion signaling that influences the metastatic potential of cancer cells.

Actins↗

PubMed2004

On-line learning through simple perceptron learning with a margin.

We analyze a learning method that uses a margin kappa a la Gardner for simple perceptron learning. This method corresponds to the perceptron learning when kappa = 0 and to the Hebbian learning when kappa = infinity. Nevertheless, we found that the generalization ability of the method was superior to that of the perceptron and the Hebbian methods at an early stage of learning. We analyzed the asymptotic property of the learning curve of this method through computer simulation and found that it was the same as for perceptron learning. We also investigated an adaptive margin control method.

Learning↗

PubMed2004

Impact of deviation from precise balance of spike-timing-dependent plasticity.

Recent biological experimental findings have shown that synaptic plasticity depends on the relative timing of pre- and post-synaptic spikes and this is called spike-timing-dependent plasticity (STDP). Many authors have claimed that a precise balance between long-term potentiation (LTP) and long-term depression (LTD) of STDP is crucial in the storage of spatio-temporal patterns. Some authors have numerically investigated the impact of an imbalance between LTP and LTD on the network properties. However, the mathematical mechanism remains unknown. We analytically show that an associative memory network has the robust retrieval properties of spatio-temporal patterns, and these properties make the network less vulnerable to any deviation from a precise balance between LTP and LTD when the network contains a finite number of neurons.

Action Potentials↗

PubMed2004

Mixed states on neural network with structural learning.

We investigated the properties of mixed states in a sparsely encoded associative memory model with a structural learning method. When mixed states are made of s memory patterns, s types of mixed states, which become equilibrium states of the model, can be generated. To investigate the properties of s types of the mixed states, we analyzed them using the statistical mechanical method. We found that the storage capacity of the memory pattern and the storage capacity of only a particular mixed state diverge at the sparse limit. We also found that the threshold value needed to recall the memory pattern is nearly equal to the threshold value needed to recall the particular mixed state. This means that the memory pattern and the particular mixed state can be made to easily coexist at the sparse limit. The properties of the model obtained by the analysis are also useful for constructing a transform-invariant recognition model.

Algorithms↗

PubMed2004

Associative memory by recurrent neural networks with delay elements.

The synapses of real neural systems seem to have delays. Therefore, it is worthwhile to analyze associative memory models with delayed synapses. Thus, a sequential associative memory model with delayed synapses is discussed, where a discrete synchronous updating rule and a correlation learning rule are employed. Its dynamic properties are analyzed by the statistical neurodynamics. In this paper, we first re-derive the Yanai-Kim theory, which involves macrodynamical equations for the dynamics of the network with serial delay elements. Since their theory needs a computational complexity of O(L4t) to obtain the macroscopic state at time step t where L is the length of delay, it is intractable to discuss the macroscopic properties for a large L limit. Thus, we derive steady state equations using the discrete Fourier transformation, where the computational complexity does not formally depend on L. We show that the storage capacity alphaC is in proportion to the delay length L with a large L limit, and the proportion constant is 0.195, i.e. alphaC=0.195L. These results are supported by computer simulations.

Association Learning↗

PubMed2004

Storage capacity diverges with synaptic efficiency in an associative memory model with synaptic delay and pruning.

It is known that storage capacity per synapse increases by synaptic pruning in the case of a correlation-type associative memory model. However, the storage capacity of the entire network then decreases. To overcome this difficulty, we propose decreasing the connectivity while keeping the total number of synapses constant by introducing delayed synapses. In this paper, a discrete synchronous-type model with both delayed synapses and their prunings is discussed as a concrete example of the proposal. First, we explain the Yanai-Kim theory by employing statistical neurodynamics. This theory involves macrodynamical equations for the dynamics of a network with serial delay elements. Next, considering the translational symmetry of the explained equations, we rederive macroscopic steady-state equations of the model by using the discrete Fourier transformation. The storage capacities are analyzed quantitatively. Furthermore, two types of synaptic prunings are treated analytically: random pruning and systematic pruning. As a result, it becomes clear that in both prunings, the storage capacity increases as the length of delay increases and the connectivity of the synapses decreases when the total number of synapses is constant. Moreover, an interesting fact becomes clear: the storage capacity asymptotically approaches 2/pi due to random pruning. In contrast, the storage capacity diverges in proportion to the logarithm of the length of delay by systematic pruning and the proportion constant is 4/pi. These results theoretically support the significance of pruning following an overgrowth of synapses in the brain and may suggest that the brain prefers to store dynamic attractors such as sequences and limit cycles rather than equilibrium states.

Action Potentials↗

PubMed2004

DREG, a developmentally regulated G protein-coupled receptor containing two conserved proteolytic cleavage sites.

We have identified and characterized a novel member of the G protein-coupled receptor (GPCR) family, termed DREG. DREG belongs to the LNB-TM7 subfamily and possesses a long amino-terminus that contains a CUB domain, a PTX domain, a hormone binding domain and a GPCR proteolytic site (GPS) domain. RT-PCR experiments and whole mount in situ hybridization in mice showed that DREG is expressed at high levels in the heart and somite during embryogenesis and in the adult lung. When DREG was transiently expressed in mammalian cultured cells, a 35-kD fragment was generated by endogenous proteolytic processing at the conserved GPS domain. This short fragment was found associated with the cell membrane, typical of GPCRs. DREG was further cleaved in the middle of the extracellular domain, generating a soluble 70-kD fragment containing the CUB and PTX domains. This processing was inhibited by an inhibitor of the endoprotease furin but not of matrix metalloproteinases. These results raise the possibility that DREG plays a role in development, not only as a receptor or an adhesion molecule but also as a secreted ligand.

Alternative Splicing↗

PubMed2004

A network model of perceptual suppression induced by transcranial magnetic stimulation.

We modeled the inhibitory effects of transcranial magnetic stimulation (TMS) on a neural population. TMS is a noninvasive technique, with high temporal resolution, that can stimulate the brain via a brief magnetic pulse from a coil placed on the scalp. Because of these advantages, TMS is extensively used as a powerful tool in experimental studies of motor, perception, and other functions in humans. However, the mechanisms by which TMS interferes with neural activities, especially in terms of theoretical aspects, are totally unknown. In this study, we focused on the temporal properties of TMS-induced perceptual suppression, and we computationally analyzed the response of a simple network model of a sensory feature detector system to a TMS-like perturbation. The perturbation caused the mean activity to transiently increase and then decrease for a long period, accompanied by a loss in the degree of activity localization. When the afferent input consisted of a dual phase, with a strong transient component and a weak sustained component, there was a critical latency period of the perturbation during which the network activity was completely suppressed and converged to the resting state. The range of the suppressive period increased with decreasing afferent input intensity and reached more than 10 times the time constant of the neuron. These results agree well with typical experimental data for occipital TMS and support the conclusion that dynamical interaction in a neural population plays an important role in TMS-induced perceptual suppression.

Afferent Pathways↗

PubMed2004

Investigation of possible neural architectures underlying information-geometric measures.

A novel analytical method based on information geometry was recently proposed, and this method may provide useful insights into the statistical interactions within neural groups. The link between informationgeometric measures and the structure of neural interactions has not yet been elucidated, however, because of the ill-posed nature of the problem. Here, possible neural architectures underlying information-geometric measures are investigated using an isolated pair and an isolated triplet of model neurons. By assuming the existence of equilibrium states, we derive analytically the relationship between the information-geometric parameters and these simple neural architectures. For symmetric networks, the first- and second-order information-geometric parameters represent, respectively, the external input and the underlying connections between the neurons provided that the number of neurons used in the parameter estimation in the log-linear model and the number of neurons in the network are the same. For asymmetric networks, however, these parameters are dependent on both the intrinsic connections and the external inputs to each neuron. In addition, we derive the relation between the information-geometric parameter corresponding to the two-neuron interaction and a conventional cross-correlation measure. We also show that the information-geometric parameters vary depending on the number of neurons assumed for parameter estimation in the log-linear model. This finding suggests a need to examine the information-geometric method carefully. A possible criterion for choosing an appropriate orthogonal coordinate is also discussed. This article points out the importance of a model-based approach and sheds light on the possible neural structure underlying the application of information geometry to neural network analysis.

Action Potentials↗

PubMed2003

Robustness of retrieval properties against imbalance between long-term potentiation and depression of spike-timing-dependent plasticity.

Spike-timing-dependent plasticity (STDP) has recently been shown in some physiological studies. STDP depends on the precise temporal relationship of presynaptic and postsynaptic spikes. Many authors have indicated that a precise balance between long-term potentiation (LTP) and long-term depression (LTD) of STDP is significant for a stable learning. However, a situation in which the balance is maintained precisely is inconceivable in the brain. Using a method of the statistical neurodynamics, we show robust retrieval properties of spatiotemporal patterns in an associative memory model against the imbalance between LTP and LTD. When the fluctuation of LTD is assumed to obey a Gaussian distribution with mean 0 and variance delta(2), the storage capacity takes a finite value even at large delta. This means that the balance between LTP and LTD of STDP need not be maintained precisely, but must be maintained on average. Furthermore, we found that the basin of attraction becomes smaller as delta increases while an initial critical overlap remains unchanged.

Animals↗

PubMed2003

Transmembrane phosphoprotein Cbp senses cell adhesion signaling mediated by Src family kinase in lipid rafts.

Cbp, a C-terminal Src kinase (Csk)-binding protein, is a transmembrane phosphoprotein that has been implicated in the regulation of the Src family kinase (SFK) through recruiting Csk, a negative regulator of SFK, to a membrane microdomain of lipid rafts. To examine the contribution of Cbp to cell adhesion signaling mediated by SFK, we investigated the kinase responsible for phosphorylating Cbp and the mode of phosphorylation during the cell adhesion process. The results obtained by using mutant mice or cells that lack Csk and/or a member of SFK, Fyn, reveal that Cbp is phosphorylated predominantly by raft-localized Fyn in vivo. Upon cell adhesion onto fibronectin, Cbp becomes transiently phosphorylated (consistent with SFK activation) and recruits Csk to lipid rafts. These events are completed before the full activation of focal adhesion kinase, indicating that the transient activation and down-regulation of SFK in lipid rafts are earlier events in cell adhesion signaling. In Csk-deficient cells, continuous hyperactivation of SFK leads to continuous hyperphosphorylation of Cbp, accompanied by impaired cell spreading and migration. Silencing of Cbp by RNA interference also induced impaired cell spreading. These findings suggest that Cbp could serve as a sensor of SFK activity in early stages of cell adhesion signaling, and that Csk-mediated down-regulation of SFK is essential to allow dynamic cellular events involved in the regulation of cell spreading and migration.

Animals↗