[11:00-11:30] Dynamical Robustness of Coupled Oscillator Networks
Speaker: Gouhei Tanaka
[11:30-12:00] Dynamical Behavior in Coupled Heterogeneous Excitable Phase Oscillators
Speaker: Kai Morino
[13:00-13:30] iPS Cell Technology for the Study of Living Neural Network
Speaker: Kenta Shimba
[13:30-13:45] Improvement and Evaluation of Brain Function Measurement Method Using Near Infrared Light
Speaker: Yasuaki Niwano
[13:45-14:00] Response of Alpha Wave and Pupil Diameter to Controlled Light Stimulus
Speaker: Yuya Kobayashi
[14:10-15:10] A Robust Neural Integrator Based on the Interactions of Three Time Scales (*)
Speaker: Bard Ermentrout
[15:20-15:50] Optimal Model Selection for Extended Dynamic Mode Decomposition
Speaker: Wataru Kurebayashi
[15:50-16:20] Synchronization of Hybrid Nonlinear Oscillators
Speaker: Sho Shirasaka
[16:30-17:00] Mean Field Dynamics of Delay-coupled Population of Modified Theta Neuron
Speaker: Akihiko Akao
[17:00-17:30] Inferring Phase Oscillator Models from Empirical Data of Frog Choruses
Speaker: Ikkyu Aihara
RCAST, Building. 3, Mezzanine 2F, Seminar room #1
http://www.rcast.u-tokyo.ac.jp/home/access/index_en.html
[AM11:00-AM11:30] Dynamical Robustness of Coupled Oscillator Networks
Speaker: Gouhei Tanaka, Authors: Gouhei Tanaka, Kai Morino, Tianyu Yuan, Kazuyuki Aihara
Abstract: Network robustness is one of the major topics in complex network theory. We have been working on dynamical robustness of complex networks, which indicates how tolerant the dynamical behavior on networks is against local perturbation. Using coupled oscillator networks, we have revealed several properties of dynamical robustness, which are different from those of structural robustness. In this talk, we introduce recent developments of theory and applications of the dynamical robustness framework.
[AM11:30-AM12:00] Dynamical Behavior in Coupled Heterogeneous Excitable Phase Oscillators
Speaker: Kai Morino, Authors: Kai Morino, Gouhei Tanaka, Kazuyuki Aihara
Abstract: Models of coupled oscillators have been widely used to understand physical, biological, and technological phenomena. Dynamical robustness of networks against local perturbation has been also studied by using coupled oscillators. Various studies on dynamical robustness have revealed how networks are fragile or robust based on types of oscillators and types of network structures. In this talk, in relationship to dynamical robustness, we show our recent studies on the dynamical behavior of coupled heterogeneous excitable phase oscillators.
[AM13:00-AM13:30] iPS Cell Technology for the Study of Living Neural Network
Speaker: Kenta Shimba
Abstract: Integration of mathematical and experimental approaches leads to exact understanding of neural dynamics. In experiment, living cultured neurons have been widely used for studying neural properties at molecular, single cell, and network levels. Moreover, recent progresses in induced pluripotent stem (iPS) cell technologies make it possible to generate characteristic neuronal populations. In this talk, we introduce how various neuronal populations can be selectively generated from iPS cells. We then show our latest study using neuronal networks with excitatory- or inhibitory- rich populations.
[PM13:30-PM13:45] Improvement and Evaluation of Brain Function Measurement Method Using Near Infrared Light
Speaker: Yasuaki Niwano
Abstract: Due to the difference in extinction coefficient and the participation state of hemoglobin and the permeability to skin and skull, the brain function measurement method using near infrared light has been widely used in recent years. Among them, absolute amount measurement is possible and expected in the method using time resolved spectroscopy. In this talk, we introduce about the current situation of time resolved spectroscopy with near infrared light, improvement and evaluation of current method.
[PM13:45-AM14:00] Response of Alpha Wave and Pupil Diameter to Controlled Light Stimulus
Speaker: Yuya Kobayashi
Abstract: Alpha wave (8-13Hz) is often observed in occipital lobe, and many studies suggest the relationship to information processing of visual system.Though there are many studies about the relationship between cognitive function and alpha wave, mechanical property of alpha wave is not well understood. In this time, we built an experimental system that enables us to present quantitative light stimulus.This system uses dark room to exclude the influence of ambient light, and obtain information about subject’s eyes by infrared cameras. By using this, we record the response of alpha wave and pupil diameter, and consider the property of oscillation and the way of signal transfer.
[AM14:10-AM15:10] A Robust Neural Integrator Based on the Interactions of Three Time Scales (*)
Speaker: Bard Ermentrout
Abstract: Neural integrators are circuits that are able to code analog information such as spatial location or amplitude. Storing amplitude requires the network to have a large number of attractors. In classic models with recurrent excitation, such networks require very careful tuning to behave as integrators and are not robust to small mistuning of the recurrent weights. In this talk, I introduce a circuit with recurrent connectivity that has is subjected to a slow subthreshold oscillation (such as the theta rhythm in the hippocampus). I show that such a network can robustly maintain many discrete attracting states. Furthermore, the firing rates of the neurons in these attracting states are much closer to those seen in recordings of animals. I show the mechanism for this can be explained by the instability regions of the Mathieu equation. I then extend the model in various ways and, for example, show that in a spatially distributed network, it is possible to code location and amplitude simultaneously.
(*): Title changed from "Scent and Sensibility"
[AM15:20-AM15:50] Optimal Model Selection for Extended Dynamic Mode Decomposition
Speaker: Wataru Kurebayashi
Dynamic mode decomposition (DMD) is a method for the mode decomposition of time series data based on the Koopman operator theory, which models the latent nonlinear dynamics underlying data in terms of the dynamical systems theory. Recently, some extended versions of the DMD [M. Williams et al., 2015; 2016], which significantly widen the applicability of this method, have been proposed. However, selecting the optimal version and parameters of the extended DMD for given data is still an open question. In my talk, I introduce our latest research, in which we propose a criterion for optimal tuning of the extended DMD.
[AM15:50-AM16:20] Synchronization of Hybrid Nonlinear Oscillators
Speaker: Sho Shirasaka Authors: Sho Shirasaka, Wataru Kurebayashi, Hiroya Nakao
Abstract: Dynamical systems involving a mixture of continuous and discrete dynamics, called hybrid dynamical systems, have used to model various rhythmic phenomena characterized by multiple distinct time scales. However, the phase reduction theory, a fundamental framework for analyzing the synchronization of limit-cycle oscillations in rhythmic systems, has mostly been restricted to continuous dynamical systems. In this talk, we introduce a general phase reduction theory for weakly perturbed limit cycles in hybrid dynamical systems that facilitates analysis, control, and optimization of systems of nonlinear oscillators whose continuous models are unavailable or intractable. As an illustration, we analyze synchronization dynamics of hybrid limit-cycle oscillators such as bipedal walkers using our proposed theory.
[AM16:30-AM17:00] Mean Field Dynamics of Delay-coupled Population of Modified Theta Neuron
Speaker: Akihiko Akao
Abstract: Collective rhythms which emerges from neuronal population are found widely in brain activities. Neuronal populations are interacting each other through delayed coupling in case of multi-regional interactions such as thalamocortical loop. However, mathematical analysis of such delay-coupled neuronal population was restricted due to the infinite dimensionality of delay differential equations. Here, we analyze the dynamics of delay-coupled population of modified theta neuron. We derive mean field dynamics as a set of delay differential equations using a dimension reduction technique called Ott-Antonsen ansatz.We analyze the emergence of collective rhythm in the derived mean field model.
[AM17:00-AM17:30] Inferring Phase Oscillator Models from Empirical Data of Frog Choruses
Speaker: Ikkyu Aihara, Authors: Ikkyu Aihara, Kaiichiro Ota, Toshio Aoyagi
Abstract: Synchronization phenomena are ubiquitous in real worlds such as flashing of fireflies and oscillations of metronomes. Here, we study the mechanisms of synchronization inherent in frog choruses by inferring phase oscillator models from empirical data. The phase-oscillator models with general interaction terms are first identified from audio data of actual male Japanese tree frogs according to a Bayesian approach; the attentions paid among the male frogs are quantified from the identified models; the effects of behavioral parameters on the attentions are analyzed by a statistical model. Consequently, we reveal the significant relationship between the attentions and behavioral parameters in the frog choruses.
Akihiko Akao
akao@neuron.t.u-tokyo.ac.jp